MU-MIMO-OFDMA METHODS AND SYSTEMS FOR SIGNALING MULTI-RANK CQIs AND PRECODERS

ABSTRACT

A method for determining attributes of communication channels of multi-user (MU)-multiple input multiple output (MIMO) users in an orthogonal frequency division multiplexing based multiple access (OFDMA) system is disclosed. The method comprises receiving from a base station, for at least one sub-band of contiguous sub-carriers, an indication of an estimate of or an upper-bound on a total number of streams that are co-scheduled by the base station on the at least one sub-band or an indication of a fraction of a transmit power at the base station that is applied to streams that are scheduled for transmission to a particular user, determining one or more signal quality measures for the at least one sub-band based on at least one of the fraction or the estimate of or the upper-bound on the total number of streams that are scheduled by the base station on the at least one sub-band, and transmitting to the base station an indication of the one or more signal quality measures. Other methods, apparatuses, and systems also are disclosed.

RELATED APPLICATION INFORMATION

This application is a divisional of co-pending U.S. patent applicationSer. No. 13/080,416 filed Apr. 5, 2011, the contents of which areincorporated herein by reference. U.S. patent application Ser. No.13/080,416 in turn claims priority to provisional application Ser. No.61/320,908 filed on Apr. 5, 2010, provisional application Ser. No.61/389,492 filed on Oct. 4, 2010 and provisional application Ser. No.61/407,243 filed on Oct. 27, 2010, the contents of all of which areincorporated herein by reference.

This application is also related to U.S. utility application Ser. No.12/642,047 filed on Dec. 18, 2009 and U.S. utility application Ser. No.12/642,126 filed on Dec. 18, 2009, the contents of all of which areincorporated herein by reference.

This application is also related to application Ser. No. 13/080,374(Attorney Docket Number 09107 (449-192), entitled ‘MU-MIMO-OFDMA SYSTEMSAND METHODS FOR MULTI-RANK CQI COMPUTATION AND PRECODER SELECTION’), andapplication Ser. No. 13/080,403 (Attorney Docket Number 10061 (449-194),entitled ‘MU-MIMO-OFDMA METHODS AND SYSTEMS FOR SIGNALING MULTI-RANKCQIs AND PRECODERS’), the contents of all of which are incorporatedherein by reference.

BACKGROUND

1. Technical Field

The present invention relates to orthogonal frequency-divisionmultiplexing based multiple access (OFDMA) multi-user (MU)-multipleinput multiple output (MIMO) systems and, more particularly, to thedetermination and transmission of scheduling information and/orparameters related thereto for MU-MIMO users in such systems.

2. Description of the Related Art

In OFDMA MU (multi-user)-MIMO (multiple-input multiple-output) systems,each active user reports a preferred precoder matrix index (PMI), whichidentifies a specific vector (or matrix) in a code-book of unit normvectors (or matrices) used to encode signals between the base stationand users. Further, each user can report a channel quality index (CQI)to the base station, which, in turn, can use the PMI and CQI todetermine an appropriate set of scheduled users and schedulingparameters for each user. The base station provides each scheduled userwith its scheduling parameters indicating assigned resource blocks thatcomprise a set of subcarriers and OFDM symbols and that are used totransmit data to the respective scheduled user.

SUMMARY

One embodiment is directed to a method for determining attributes ofcommunication channels of MU-MIMO users in an OFDMA system. The methodincludes receiving from a base station, for at least one sub-band ofcontiguous sub-carriers, an indication of an estimate of or anupper-bound on a total number of streams that are co-scheduled by thebase station on the at least one sub-band or an indication of a fractionof a transmit power at the base station that is applied to streams thatare scheduled for transmission to a particular user. The method furtherincludes determining one or more signal quality measures for the atleast one sub-band based on at least one of the fraction or the estimateof or the upper-bound on the total number of streams that are scheduledby the base station on the at least one sub-band. In addition, anindication of the one or more signal quality measures is transmitted tothe base station in the method.

Another embodiment is directed to a method for determining precoders forcommunication channels of MU-MIMO users in an OFDMA system. The methodincludes receiving from a base station, for at least one sub-band ofcontiguous sub-carriers, an indication of an estimate of or anupper-bound on a total number of streams that are co-scheduled by thebase station on the at least one sub-band or an indication of a fractionof a transmit power at the base station that is applied to streams thatare scheduled for transmission to a particular user. The method furtherincludes determining a precoder matrix for the at least one sub-bandbased on at least one of the fraction or the estimate of or theupper-bound on the total number of streams that are scheduled by thebase station on the at least one sub-band. In addition, an indication ofthe precoder matrix is transmitted to the base station in the method.

An alternative embodiment is directed to a receiver system fordetermining attributes of communication channels of MU-MIMO users in anOFDMA system. The receiver system includes a receiver that is configuredto receive from a base station, for at least one sub-band of contiguoussub-carriers, an indication of an estimate of or an upper-bound on atotal number of streams that are co-scheduled by the base station on theat least one sub-band or an indication of a fraction of a transmit powerat the base station that is applied to streams that are scheduled fortransmission to a particular user. The system further includes aprocessor that is configured to determine one or more signal qualitymeasures for the at least one sub-band based on at least one of thefraction or the estimate of or the upper-bound on the total number ofstreams that are scheduled by the base station on the at least onesub-band. In addition, the system includes a transmitter that isconfigured to transmit to the base station an indication of the one ormore signal quality measures.

These and other features and advantages will become apparent from thefollowing detailed description of illustrative embodiments thereof,which is to be read in connection with the accompanying drawings.

BRIEF DESCRIPTION OF DRAWINGS

The disclosure will provide details in the following description ofpreferred embodiments with reference to the following figures wherein:

FIG. 1 is a high-level block diagram of an exemplary OFDMA-MU-MIMOsystem in accordance with an exemplary embodiment of the presentinvention.

FIG. 2 is a high-level block/flow diagram of a base station and aMU-MIMO user in accordance with an exemplary embodiment of the presentinvention.

FIG. 3 is a flow diagram of an exemplary method for determiningattributes of communication channels of MU-MIMO users in an OFDMAsystem.

FIG. 4 is a flow diagram of an exemplary method for determining awideband precoder and corresponding channel quality indices.

FIG. 5 is a flow diagram of an exemplary method for scheduling MU-MIMOusers in an OFDMA system.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Referring now in detail to the figures in which like numerals representthe same or similar elements and initially to FIG. 1, an OFDMA basedmulti-user (MU)-multiple input multiple output (MIMO) system 100 inwhich embodiments of the present invention may be implemented isillustrated. In the downlink of system 100, multiple scheduled users(UEs) 102 in a cell 106 are simultaneously served by a base station (BS)104 on an available set of resource blocks (RBs), where each RB is aparticular set of contiguous subcarriers and consecutive OFDM symbols.

In the MU-MIMO downlink from the BS, each scheduled user is served oneor more data streams using precoding (or multi-rank beamforming). Inaccordance with one embodiment, each scheduled user is served a singledata stream using beamforming or two data streams using rank-2precoding. Each active user in the system reports a preferred matrixindex (PMI) (per sub-band) to the BS, where a sub-band is a set ofcontiguous RBs. As indicated above, the reported PMI is an index thatidentifies a particular codebook of unit norm vectors or a particularmatrix in a codebook of semi-unitary matrices. For example, the codebookcan be a codebook of semi-unitary rank-2 matrices. The codebooks areknown in advance to the BS as well as all users. Each user also reportsone or more channel quality indices (CQIs) (per sub-band), which arebased on or are its estimates of the signal-to-interference-plus-noiseratios (SINRs) on that sub-band. In one embodiment, each user reports upto two channel CQIs (per sub-band). The BS collects the PMIs and CQIsreported by all active users and then determines a suitable set of usersto schedule as well as their assigned rates. A key practical problem inthe MU-MIMO downlink is that when computing its PMI and CQIs, a userdoes not have an accurate estimate of the interference it mightexperience (if scheduled) from the signals intended for the otherco-scheduled users. Co-scheduled users comprise, for example, receiversthat are assigned at least one resource block (RB) that overlaps with atleast one RB assigned to one or more other users. In turn, co-scheduledstreams comprise, for example, streams that are transmitted on at leastone common resource block (RB). For example, co-scheduled streams can bestreams that are transmitted on a common sub-band. If the usercompletely disregards the interference it might experience, it will thenreport optimistic CQIs and consequently be unable to support the rateassigned to it by the BS post-scheduling. Thus, obtaining more accuratereports from the users is important in improving the cell throughputoffered by MU-MIMO.

To address the problem, aspects of the present principles inform user ofan indication of an estimate of (or an upper bound on) the total numberof streams (s) that the base station will schedule on a sub-band.Additionally or alternatively, to further aid in enabling users todetermine accurate PMI and CQI estimates, embodiments can also inform aparticular user of one or more of the following: a suggested precodingmatrix rank (r), a maximum rank (r_(max)) for the particular user, anestimate of the per-RB total power (ρ) of signals transmitted to allusers co-scheduled with the particular user, the fraction (α) of thetotal power that will be employed for the data signals directed to theparticular user, or any combination thereof. Further, embodiments canemploy a variety of signaling schemes that convey such information tothe user, as described in more detail herein below. Moreover, severalmethods of determining the PMI and CQI, based on the SINR, that use suchconveyed parameters are also described. These methods significantlyenhance the user's ability to reduce the mismatch between the SINR onwhich the user's report to the base station is based and the SINR theuser actually observes after scheduling.

Referring to FIG. 2, with continuing reference to FIG. 1, exemplaryimplementations of a base station system 104 and a MU-MIMO receiversystem 102 are illustrated. The base station 104 may include a scheduler204 and a controller 206, while the user 102 can include processor 210.The controller 206 and processor 210 can use respective storage mediumsprovided in the base station 104 and receiver 102. In addition, the basestation 104 and the receiver 102 can include transmitters/receivers 208and 212, respectively, for the transmission and reception of controlsignals. The user 102 can transmit control signals to the base station104 on one or more uplink control channels 202 and the base station 104can transmit control signals to the user 102 on one or more downlinkcontrol channels 205. The elements of the base station 104 and theMU-MIMO receiver 102 are discussed in more detail below with respect tomethod embodiments.

It should be noted that embodiments described herein may be entirelyhardware, entirely software or including both hardware and softwareelements. In a preferred embodiment, the present invention isimplemented in hardware and software, which includes but is not limitedto firmware, resident software, microcode, etc.

Embodiments may include a computer program product accessible from acomputer-usable or computer-readable medium providing program code foruse by or in connection with a computer or any instruction executionsystem. A computer-usable or computer readable medium may include anyapparatus that stores, communicates, propagates, or transports theprogram for use by or in connection with the instruction executionsystem, apparatus, or device. The medium can be magnetic, optical,electronic, electromagnetic, infrared, or semiconductor system (orapparatus or device) or a propagation medium. The medium may include acomputer-readable storage medium such as a semiconductor or solid statememory, magnetic tape, a removable computer diskette, a random accessmemory (RAM), a read-only memory (ROM), a rigid magnetic disk and anoptical disk, etc.

A data processing system suitable for storing and/or executing programcode may include at least one processor coupled directly or indirectlyto memory elements through a system bus. The memory elements can includelocal memory employed during actual execution of the program code, bulkstorage, and cache memories which provide temporary storage of at leastsome program code to reduce the number of times code is retrieved frombulk storage during execution. Input/output or I/O devices (includingbut not limited to keyboards, displays, pointing devices, etc.) may becoupled to the system either directly or through intervening I/Ocontrollers.

Network adapters may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modem and Ethernet cards are just a few of thecurrently available types of network adapters.

Referring now to FIG. 3, with continuing reference to FIGS. 1 and 2, anexemplary method 300 for determining and conveying coding parameters andattributes of communication channels of multi-user (MU)-multiple inputmultiple output (MIMO) users in an orthogonal frequency divisionmultiple access (OFDMA) system. Any of the users 102 can be configuredto implement the method 300. In accordance with the method, the receiver212, at step 302, can receive scheduling parameters for one or moresub-bands from, for example, the base station 104. For example, asstated above, the receiver 212 can receive an indication of any one ormore of an estimate of (or an upper bound on) the total number ofstreams (S) that the base station will schedule on a sub-band, asuggested precoding matrix rank (r) for the particular user 102, amaximum rank (r_(max)) for the particular user 102, an estimate of theper-RB total power (ρ) of signals transmitted to all users co-scheduledwith the particular user 102 and the fraction (α) of the total powerthat will be employed for the data signals directed to the particularuser 102.

At step 304, the processor 210 can determine a PMI and/or SINR based onany one or more of the received parameters. Several differentimplementations of the determination step 304 are described in moredetail herein below.

At step 306, the processor 210 can direct the transmitter 212 totransmit indication(s) of the determined PMI and/or SINR. For example,the receiver 102 can transmit the PMI and a CQI based on the SINR to thebase station 104. Here, the processor 210 can determine the CQI by, forexample, using a look up table correlating CQIs with SINRs stored in thestorage medium at the receiver 102.

1. PMI Selection and CQI Computation Rules

Prior to discussing detailed schemes for implementing the PMI/CQIdetermination step 304, an exemplary model of the signal received by theuser 102 is described. Consider the narrowband received signal model ata user terminal of interest that is equipped with N receive antennas andwhere the base station 104 (e.g., eNodeB) has M transmit antennas,

y=H ^(†) x+η,  (1)

where HεC^(M×N) is the channel matrix and N˜C

(0, I) is the additive noise. The signal vector x transmitted by theeNodeB can be expanded as

$\begin{matrix}{x = {\sum\limits_{k \in U}{V_{k}s_{k}}}} & (2)\end{matrix}$

where υ is the set of users that are scheduled. V_(k) is an M×r_(k)semi-unitary matrix, referred to as a transmit precoder (or transmitprecoding matrix), having M rows and r_(k) columns, with V_(k)^(†)V_(k)=I_(rk)·s_(k) is the r_(k)×1 symbol vector corresponding touser kευ. Further, let S=Σ_(kευ)r_(k) be the total number of streamsthat are co-scheduled. Here, each scheduled stream is assigned anidentical power ρ′. The controller 206 of the base station selects theset of scheduled users, υ, along with their transmit precoding matricesand assigned rates, based on the reports received from the active users.In particular, the k^(th) user reports a PMI that identifies aquantization matrix which is a semi-unitary matrix G_(k) (having M rowsand R_(k) columns) from a codebook of such matrices. In addition, theuser also reports up-to R_(k) CQIs. Based on these reports, thecontroller 206 of the base station 104 selects a set υ of users thathave reported mutually (near-)orthogonal matrices or vectors{G_(k)}_(kευ) and which, optionally, also yield a high weighted sumrate. The controller 206 can then determine the transmit precodingmatrices and rates for the selected users. For example, controller 206can either set V_(k)=G_(k)∀kευ or it can perform a block diagonalizationtechnique on {G_(k)}_(kευ) to determine {V_(k)}_(kευ). Note that r_(k)is the number of streams that are used to serve user k and it is lessthan or equal to R_(k).

The processor 210 of the user of interest 102 can estimate ρ′H. It canbe assumed that the user of interest also has an estimate of Savailable. In practice, the base station 104 can convey an estimate of S(or an upper bound on S) to a user in a semi-static manner and such anestimate can be user-specific. The user can then use its estimates ofρ′H and S as described further herein below to select PMIs and tocompute SINRs.

It should be noted that the only information the BS 104 has about thechannel seen by a particular user k in this example is through G_(k) andthe (up-to) R_(k) CQIs. Thus, the transmit precoding matrices that areconstructed by the BS 104 may result in interference at the user end andthe rate assigned by it may also not be supportable by the user. Therate supportable by a scheduled user in the aftermath of schedulingdepends on the set of all assigned transmit precoding matrices. Thissupportable rate can thus not be exactly conveyed by the user in its CQIreports, as, at that instance, the user is unaware of the set of allassigned transmit precoding matrices. As stated above, to address theproblem, the BS 104 can convey to each active user, an estimate of (oran upper bound on) the total number of streams that it expects toschedule on a sub-band. This number can be user-specific. In addition,the BS can also convey a suggested rank value to each active user. Inaccordance with one aspect, a user that does not receive a suggestedrank value (or equivalently receives a rank value implying‘no-restriction’) is free to select a quantization precoder of any rank,whereas the one that receives a suggested rank, selects a quantizationprecoder having the suggested rank. Together, these parameters permitthe user to better account for the interference it might observepost-scheduling and hence report more accurate CQIs.

2. PMI Selection and SINR Computation Schemes and Rules

Preliminarily, the case in which the user reports one PMI along with oneor more CQIs (each based on a computed SINR) is considered. In generalthe PMI can correspond to a precoder of rank r, where 1≦r≦min{M, N}. Inthe scenario where fast-rank adaptation is permitted in MU-MIMO, todetermine the PMI at step 304, the processor 210 of the user 102 candetermine the best precoder for each value of r and can then select theprecoder which yields the overall highest rate. In the case where onlyslow rank adaptation is permitted, the base station 104 can inform theuser about a suitable r in a semi-static manner and the processor 210 ofthe user 102 then selects a precoder matrix of that rank.

Next, in order to determine a suitable semi-unitary matrix Ĝ_(r), from aset or codebook of rank-r semi-unitary matrices, C_(r), and/or up-to rSINRs, the processor 210 of the user of interest can use any one or moreof the following schemes. In particular, the following schemes andcomputations can be performed by the processor 210 to implement thedetermination step 304 of the method 300 described above. One feature ofthe schemes and rules derived below is that they attempt to account forthe interference due to signals intended for the co-scheduled users andmaximize a bound on the expected SINR or the expected capacity.

For example, in one implementation, the user 102 can select the PMIbased on a capacity metric. Here, the user 102 can select the PMI asfollows:

$\begin{matrix}\begin{matrix}{{\hat{G}}_{r} = {\arg \; {\max\limits_{G \in C_{r}}\left\{ {\ln {{I + {\rho^{\prime}G^{\dagger}{H\left( {I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H}} \right)}^{- 1}H^{\dagger}G}}}} \right\}}}} \\{= {\arg \; {\max\limits_{G \in C_{r}}\begin{Bmatrix}{{\ln {{I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} + {\rho^{\prime}H^{\dagger}{GG}^{\dagger}H}}}} -} \\{\ln {{I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H}}}}\end{Bmatrix}}}}\end{matrix} & (3) \\{{{where}\mspace{14mu} \overset{\sim}{\rho}} = \frac{\rho^{\prime}\left( {S - r} \right)}{M - r}} & \;\end{matrix}$

and ρ′ is the power-per-stream and can be assumed to be ρ/S with ρ beingthe total power. The descriptions of {tilde over (ρ)} and ρ′ also applyto the implementations of PMI selection and CQI computation schemes andrules described herein below, unless noted otherwise.

In an alternative implementation, which can be employed in MMSE (minimummean square error) based receivers, the user 102 can select the PMIafter determining r SINRs for each matrix in C_(r). Let G=[g₁, . . . ,g_(r)]. To select the PMI, the user 102 can compute the following,G=[g₁, . . . , g_(r)].

$\begin{matrix}{\mspace{20mu} {{{\hat{G}}_{r} = {\arg \; {\max\limits_{G \in C_{r}}\left\{ {\sum\limits_{j = 1}^{r}{\ln \left( {1 + {{SINR}_{j,r}^{MMSE}(G)}} \right)}} \right\}}}}\mspace{20mu} {where}}} & (4) \\{{{SINR}_{j,r}^{MMSE}(G)} = \frac{\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}\; H^{\dagger}H} + {\left( {\rho^{\prime} - \overset{\sim}{\rho}} \right)H^{\dagger}{GG}^{\dagger}H}} \right)}^{- 1}H^{\dagger}g_{j}}{1 - {\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}\; H^{\dagger}H} + {\left( {\rho^{\prime} - \overset{\sim}{\rho}} \right)H^{\dagger}{GG}^{\dagger}H}} \right)}^{- 1}H^{\dagger}g_{j\;}}}} & (5)\end{matrix}$

In another implementation, which can be employed in an SIC (successiveinterference cancellation), the user 102 can also select a PMI afterdetermining r SINRs for each matrix in C_(r). Here, we let G=[g₁, . . ., g_(r)] and suppose the order of decoding to be {1, . . . , r}. Toselect the PMI, the user 102 can compute the following:

$\begin{matrix}{\mspace{79mu} {{{\hat{G}}_{r} = {\arg {\max\limits_{G \in C_{r}}\left\{ {\sum\limits_{j = 1}^{r}\; {\ln \left( {1 + {{SINR}_{j,r}^{SIC}(G)}} \right)}} \right\}}}}\mspace{79mu} {where}}} & (6) \\{{{SINR}_{j,r}^{SIC}(G)} = \frac{\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} + {\rho^{\prime}H^{\dagger}{\sum\limits_{q = j}^{r}\; {g_{q}g_{q}^{\dagger}H}}}} \right)}^{- 1}H^{\dagger}g_{j}}{1 - {\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} + {\rho^{\prime}H^{\dagger}{\sum\limits_{q = j}^{r}\; {g_{q}g_{q}^{\dagger}H}}}} \right)}^{- 1}H^{\dagger}g_{j}}}} & (7)\end{matrix}$

It should be noted that, using the chain rule,

${\sum\limits_{j = 1}^{r}\; {\ln \left( {1 + {{SINR}_{j,r}^{SIC}(G)}} \right)}} = {{\ln {{I + {\overset{\sim}{\rho}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} + {\rho^{\prime}H^{\dagger}{GG}^{\dagger}H}}}} - {\ln {{I + {\overset{\sim}{\rho}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H}}}}}$

so that the user 102 can compute an optimal PMI use using (3) and canthen compute r SINRs for the Ĝ_(r), so determined.

In accordance with another implementation, which can employ a singleunified SINR for an MMSE receiver when r>1, the user 102 can select aPMI after determining one SINR for each matrix in C_(r). We let G=[g₁, .. . , g_(r)]. Accordingly, the user 102 can compute the precoder and theSINR as follows

$\begin{matrix}\begin{matrix}{\mspace{79mu} {{{\hat{G}}_{r} = {\arg {\max\limits_{G \in C_{r}}\left\{ {\ln \left( {1 + {{SINR}_{j,r}^{MMSE}(G)}} \right)} \right\}}}}\mspace{79mu} {where}}} \\{{\ln \left( {1 + {{SINR}_{j,r}^{MMSE}(G)}} \right)} = {{\ln {{I + {\overset{\sim}{\rho}H^{\dagger}H} + {\left( {\rho^{\prime} - \overset{\sim}{\rho}} \right)H^{\dagger}{GG}^{\dagger}H}}}} - {\ln {{I + {\overset{\sim}{\rho}H^{\dagger}H} + {\left( {\frac{\rho^{\prime}\left( {r - 1} \right)}{r} - \overset{\sim}{\rho}} \right)H^{\dagger}{GG}^{\dagger}H}}}}}}\end{matrix} & (8)\end{matrix}$

In an alternate scheme for MMSE based receivers, the user 102 can selecta PMI after determining r SINRs for each matrix in C_(r). We let G=[g₁,. . . , g_(r)]. Here, for each choice of precoder G we consider theworst possible interferers scheduled along S-r vectors in the M−rdimensional null-space of G^(†) subject to some constraints. Inparticular,

$\mspace{85mu} {{\hat{G}}_{r} = {\arg {\max\limits_{G \in C_{r}}{\min\limits_{U \in {C^{{({M - r})} \times {({S - r})}}:{{UU}^{\dagger}I}}}\left\{ {\sum\limits_{j = 1}^{r}\; {\ln \left( {1 + {{SINR}_{j,r}^{MMSE}\left( {G,U} \right)}} \right)}} \right\}}}}}$  where${{{SINR}_{j,r}^{MMSE}\left( {G,U} \right)} = {\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\rho^{\prime}{\sum\limits_{m \neq j}\; {H^{\dagger}g_{m}g_{m}^{\dagger}H}}} + {\rho^{\prime}H^{\dagger}{QUU}^{\dagger}Q^{\dagger}H}} \right)}^{- 1}H^{\dagger}g_{j}}},\mspace{20mu} {{QQ}^{\dagger} = {I - {GG}^{\dagger}}},{{Q^{\dagger}Q} = {I.}}$

The following two special cases are particularly important.

For Rank-1 or beamforming with r=1, the user 102 can select optimalvector ĝ₁εC₁ and can compute only one SINR (per vector) in accordancewith the following. Specializing either (4) or (6) to this case, we have

$\begin{matrix}{{{\hat{g}}_{1} = {\arg {\max\limits_{g \in C_{1}}\left\{ {{SINR}_{1,1}^{MMSE}(g)} \right\}}}}{where}{{{SINR}_{1,1}^{MMSE}(g)} = {\rho^{\prime}g^{\dagger}{H\left( {I + {\overset{\sim}{\rho}{H^{\dagger}\left( {I - {gg}^{\dagger}} \right)}H}} \right)}^{- 1}H^{\dagger}g}}{{{with}\mspace{14mu} \overset{\sim}{\rho}} = {\frac{\rho^{\prime}\left( {S - 1} \right)}{M - 1}.}}} & (9)\end{matrix}$

It can be shown that the rule in (9) is equivalent to the following rulethat is much simpler to compute.

$\begin{matrix}{{\hat{g}}_{1} = {\arg {\max\limits_{g \in C_{1}}\left\{ {g^{\dagger}{H\left( {I + {\overset{\sim}{\rho}H^{\dagger}H}} \right)}^{- 1}H^{\dagger}g} \right\}}}} & (10)\end{matrix}$

For Rank-2 or precoding with r=2, the user 102 can select an optimalmatrix Ĝ₂εC₂ using the SIC formula in (6) with r=2 and can direct thefeed back of 2 CQIs based on the computed SINRs in the form of abase-CQI and a delta-CQI. Expanding Ĝ₂=[ĝ_(1,2),ĝ_(2,2)], we note thatin this case the CQI computed using first SINR, SINR_(1,2) ^(SIC)(Ĝ₂),is the base CQI. The second CQI is equal to the base-CQI plus delta-CQIand corresponds to the second SINR, SINR_(2,2) ^(SIC)(Ĝ₂). This permitsthe controller 206 of the base station 104 to perform a rank-override inwhich the user is scheduled as a rank-1 MU-MIMO user based on the pair(SINR_(2,2) ^(SIC),ĝ_(2,2)). Alternatively, the user 102 can select anoptimal matrix Ĝ₂εC₂ using the unified formula in (8) with r=2. The baseCQI can correspond to SINR₂ ^(MMSE)(Ĝ₂). The second CQI is equal to thebase-CQI plus delta-CQI and corresponds to the following SINR

$\begin{matrix}{\frac{\rho^{\prime}{\hat{g}}_{2,2}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}H^{\dagger}H}} \right)}^{- 1}H^{\dagger}{\hat{g}}_{2,2}}{1 - {\hat{\rho}{\hat{g}}_{2,2}^{\dagger}{H\left( {I + {\overset{\sim}{\rho}H^{\dagger}H}} \right)}^{- 1}H^{\dagger}{\hat{g}}_{2,2}}}{{{with}\mspace{14mu} \overset{\sim}{\rho}} = {\frac{\rho^{\prime}\left( {S - 1} \right)}{M - 1}.}}} & (11)\end{matrix}$

This permits the base station 104 to perform a rank-override in whichthe user is scheduled as a rank-1 MU-MIMO user based on ĝ_(2,2) and theSINR given in (11).

2.1 Alternate PMI Selection and CQI Computation Schemes

In accordance with an alternate PMI selection and CQI computationscheme, the user 102 can first select a matrix from C_(r) by quantizingthe r dominant right singular vectors of H^(†). In particular, letH^(†)=UΛ{tilde over (V)}^(†) be the SVD (single value decomposition) ofH^(†) where {tilde over (V)} is a M×N semi-unitary matrix. Let {tildeover (V)}_((r)) denote the matrix formed by the first r columns of{tilde over (V)} which are the r dominant right singular vectors ofH^(†). Then, the user 102 can select a matrix from C_(r) by using

$\begin{matrix}{{\hat{G}}_{r} = {\arg {\max\limits_{G \in C_{r}}\left\{ {{tr}\left( {{\overset{\sim}{V}}_{(r)}^{\dagger}G_{r}G_{r}^{\dagger}{\overset{\sim}{V}}_{(r)}} \right)} \right\}}}} & (12)\end{matrix}$

After such a Ĝ_(r) is determined, the user 102 can compute the r SINRscorresponding to Ĝ_(r) using either (5) or (7).

In accordance with another alternate PMI selection and CQI computationscheme, which can be employed for SU (single-user)-MIMO receivers, todetermine a suitable precoding matrix from C_(r) along withcorresponding SINRs, the user 102 of interest can use the followingSU-MIMO rules, which completely neglect the interference that will becaused due to other co-scheduled streams. For convenience, only the MMSEbased receiver is considered here. Then, the user 102 can select the PMIafter determining r SINRs for each matrix in C_(r), as provided below.We let G=[g₁, . . . , g_(r)].

$\begin{matrix}\begin{matrix}{\mspace{79mu} {{{\hat{G}}_{r} = {\arg {\max\limits_{G \in C_{r}}\left\{ {\sum\limits_{j = 1}^{r}\; {\ln \left( {1 + {{SINR}_{j,r}^{MMSE}(G)}} \right)}} \right\}}}}\mspace{79mu} {where}}} \\{{{SINR}_{j,r}^{MMSE}(G)} = {\frac{\rho}{r}g_{j}^{\dagger}{H\left( {I + {\frac{\rho}{r}H^{\dagger}{GG}^{\dagger}H} - {\frac{\rho}{r}H^{\dagger}g_{j}g_{j}^{\dagger}H}} \right)}^{- 1}H^{\dagger}g_{j}}}\end{matrix} & (13)\end{matrix}$

with ρ denoting the total power that is equally divided among allstreams.

2.2 Derivations of PMI Selections

The capacity metric in (3) for selecting a PMI of rank r, where 1≦r≦N,will now be derived for completeness purposes. Suppose that the user 102of interest considers reporting any PMI G_(r)εC^(M×r) to the basestation. The user 102 assumes that upon doing so, the transmit precoderemployed by the base station 104 to serve the user 102 will be V₁=G_(r)and that the user 102 will be co-scheduled with other users who in turnare served using transmit precoders that lie in the null-space of V₁^(†), i.e., V₁ ^(†)V_(k)=0, ∀k≠1. In addition, the user 102 assumes thatthere will be S-r such co-scheduled streams (intended for the otherusers) in total. Thus, the model that the user deems will be seen by itpost-scheduling is

$\begin{matrix}{{y = {{H^{\dagger}G_{r}s_{1}} + {\sum\limits_{k \neq 1}\; {H^{\dagger}V_{k}s_{k}}} + \eta}},} & (14)\end{matrix}$

where Hε⊂^(M×N) is the channel matrix and η˜C

(0, I) is the additive noise. In order to determine a rate that can beobtained over this model, the user 102 proceeds as follows. To determinethe rate, the user 102 should obtain the covariance matrix of theinterference. However, because the transmit precoders employed for theco-scheduled users are not known, the user employs an expectedcovariance matrix of the interference. This expected covariance matrixis computed after assuming that the co-scheduled streams are transmittedalong vectors that are isotropically distributed in the null space of V₁^(†). In particular, let P=G_(r)G_(r) ^(†) be an orthogonal projectionand let P_(⊥)=I−P denote its orthogonal complement. Because the rank ofG_(r) is r, we have that the rank of P_(⊥) is M-r so that it can bedecomposed as P_(⊥)=SS^(†), where Sε⊂^(M×M-r) is a semi-unitary matrixof rank M-r. Note that one choice of S can be obtained from adeterministic function of G_(r). Then, the assumption made by the user102 is that each co-scheduled stream is transmitted along a vector ofthe form Su, where u is isotropically distributed in ⊂^(M-r). Based onthis assumption, the following lemma is offered:Lemma 1 For a given H, G_(r), the expected covariance matrix of theinterference can be computed as

$\begin{matrix}{{E\left\lbrack {H^{\dagger}{\sum\limits_{k \neq 1}\; {V_{k}V_{k}^{\dagger}H}}} \right\rbrack} = {\frac{S - r}{M - r}H^{\dagger}P_{\bot}H}} & (15)\end{matrix}$

Using lemma 1, the rate computed by the user for the choice of G_(r), isgiven by

$\begin{matrix}{{\ln {{I + {\rho^{\prime}H^{\dagger}{PH}^{\dagger}} + {\rho^{\prime}{E\left\lbrack {H^{\dagger}{\sum\limits_{k \neq 1}\; {V_{k}V_{k}^{\dagger}H}}} \right\rbrack}}}}} - {\ln {{{I + {\rho^{\prime}{E\left\lbrack {H^{\dagger}{\sum\limits_{k \neq 1}\; {V_{k}V_{k}^{\dagger}H}}} \right\rbrack}}}}.}}} & (16)\end{matrix}$

Using (15) in (16) yields

$\begin{matrix}{{\ln {{I + {\rho^{\prime}H^{\dagger}{PH}} + {\rho^{\prime}\frac{S - r}{M - r}H^{\dagger}P_{\bot}H}}}} - {\ln {{I + {\rho^{\prime}\frac{S - r}{M - r}H^{\dagger}P_{\bot}H}}}}} & (17)\end{matrix}$

The user thus employs the rule in (3) which optimizes (17) over allG_(r) in the codebook of rank-r semi-unitary matrices.

3. PMI, Best-Companion-PMI Selection and CQI Computation Schemes andRules

In accordance with exemplary aspects of the present principles, theprocessor 210 of the receiver 102 can determine, at step 304 of themethod 300, a best companion PMI in addition to a selected PMI byemploying the following schemes. Here, processor 210 can feed back thePMI and the best companion PMI to the base station 104 with theunderstanding that the codeword corresponding to such a companion PMIgenerates the least amount of interference for the user. In addition toS (and possibly r), we assume that the user of interest knows (or hasbeen informed about) r^(c), the rank of the codeword to be selected asthe companion. Here, the user 102 can receive r^(c) at step 302 of themethod 300.

In accordance with one implementation, the user 102 can utilize acapacity metric to determine the PMI and the best companion PMI. Forexample, the user 102 can select a matrix Ĝ_(r) along with thebest-companion matrix, Ĝ_(r) _(c) as follows:

$\left\{ {{\hat{G}}_{r},{\hat{G}}_{r^{c}}} \right\} = {\arg {\max\limits_{{G \in C_{r}},{G_{r^{c}} \in C_{r^{c}}}}\begin{Bmatrix}{\ln {{I + {\overset{\Cup}{\rho}H^{\dagger}P_{G,G_{r^{c}}}^{\bot}H} + {\rho^{\prime}H^{\dagger}{GG}^{\dagger}H} + {\rho^{\prime}H^{\dagger}G_{r^{c}}G_{r^{c}}^{\dagger}H}}}} \\{{- \ln}{{I + {\overset{\Cup}{\rho}H^{\dagger}P_{G,G_{r^{c}}}^{\bot}H} + {\rho^{\prime}H^{\dagger}G_{r^{c}}G_{r^{c}}^{\dagger}H}}}}\end{Bmatrix}}}$$\mspace{20mu} {{{{where}\mspace{14mu} \overset{\Cup}{\rho}} = \frac{\rho^{\prime}\left( {S - r - r^{c}} \right)}{r^{\prime}}},}$

P_(G,G) ^(⊥) _(r) _(c) =I−[G,G _(r) _(c)][G,G_(r) _(c) ]⁺ is aprojection matrix and r′=Rank(P_(G,G) ¹⁹⁵ _(r) _(c) ). Note that sinceboth G, G_(r) _(c) are semi-unitary matrices, when G_(r) _(c) ^(†)G=0,we can also write P_(G,G) ^(⊥) _(r) _(c) =I−GG†−G_(r) _(c) G_(r) _(c)^(†)and in this case r′=M−r−r^(c).

In accordance with another implementation, which can be employed in anMMSE base receiver, the user 102 can select a matrix Ĝ_(r) afterdetermining r SINRs for each matrix in C_(r). The user 102 can selectthe best-companion matrix, Ĝ_(r) _(c) as follows. We let G=[g₁, . . . ,g_(r)].

$\begin{matrix}{\mspace{79mu} {{\left\{ {{\hat{G}}_{r},{\hat{G}}_{r^{c}}} \right\} = {\arg {\max\limits_{{G \in C_{r}},{G_{r^{c}} \in C_{r^{c}}}}\left\{ {\sum\limits_{j = 1}^{r}\; {\ln \left( {1 + {{SINR}_{j,r}^{MMSE}\left( {G,G_{r^{c}}} \right)}} \right)}} \right\}}}}\mspace{20mu} {where}}} & (18) \\{{{SINR}_{j,r}^{MMSE}\left( {G,G_{r^{c}}} \right)} = {\rho^{\prime}g_{j}^{\dagger}{H\left( {I + {\overset{\Cup}{\rho}H^{\dagger}P_{G,G_{r^{c}}}^{\bot}H} - {\rho^{\prime}H^{\dagger}G_{r^{c}}G_{r^{c}}^{\dagger}H} + {\rho^{\prime}H^{\dagger}{\sum\limits_{k \neq j}\; {g_{k}g_{k}^{\dagger}H}}}} \right)}^{- 1}H^{\dagger}g_{j}}} & (19)\end{matrix}$

Note that the alternate rule derived in Section 2.1 above can be readilyextended to this scenario. In particular, the user 102 first uses (12)to determine the matrix Ĝ_(r). Next, it again uses (12) to determine thematrix Ĝ_(r) _(c) , except the search is over C_(r) _(c) and {tilde over(V)}_((r)) is replaced by {circumflex over (V)}_((r) _(c) ₎, with{circumflex over (V)}_((r) _(c) ₎ denoting the M×r^(c) matrix formed bythe r^(c) right singular vectors of H^(†) that correspond to the r^(c)smallest singular values. Once Ĝ_(r), Ĝ_(r) _(c) are determined, theuser 102 can compute the r SINRs corresponding to Ĝ_(r), Ĝ_(r) _(c)using (19). Alternatively, the user 102 can compute the best companionPMI using the aforementioned rules. The user 102 can then report to thebase station 104 the CQI(s) that are based on SINR(s) without the bestcompanion (for example using (5) with Ĝ_(r)) along with a delta CQI thatcorresponds to the average difference between the SINRs without the bestcompanion and those with the best companion ((19) with Ĝ_(r), Ĝ_(r) _(c)).

4. PMI, Inter-Cell Companion-PMI Selection and CQI Computation Schemesand Rules

In accordance with embodiments of the present principles, an exemplarynarrowband received signal model at a user terminal 102 that is alsointerfered with by other base stations that do not serve the user 102can be considered. Here, in this particular example, let I denote theset of interferers.

$\begin{matrix}{y = {{H^{\dagger}x} + {\sum\limits_{q \in I}{H_{(q)}^{\dagger}x_{(q)}}} + \eta}} & (20)\end{matrix}$

where now H_((q))εC^(M) ^(q) ^(×N) is the channel matrix seen from theq^(th) interfering base station, with M_(q) being the number of transmitantennas at the q^(th) base station. Note that the signal vector x_((q))transmitted by the q^(th) base station can be expanded as

$\begin{matrix}{x_{(q)} = {\sum\limits_{m \in V_{(q)}}{V_{{(q)},m}s_{{(q)},m}}}} & (21)\end{matrix}$

where υ_((q)) is the set of users that are scheduled by the q^(th)interfering base station.

Thus, at step 306 of the method 300, the user 102 of interest can feedback to its serving base station, a PMI for the direct channel it seesfrom its serving base station 104 and a worst-companion PMI for each oneof the dominant interfering base stations. In addition to S and possiblyr, the user of interest 102 knows, for each base station q, an estimate,S_(q), of the number of streams the q^(th) interfering base stationexpects to simultaneously schedule. Further, it can be assumed that theuser of interest 102 also knows, for each base station q, r_(q), whichis the number of dimensions the q^(th) interfering base station isprepared to surrender. For example, the processor 210 of the receiver102 can, at step 302 of the method 300, receive from the serving basestation 104 S_(q) and r_(q) for each interfering base station q. Inparticular, given r_(q), at step 304 of the method 300, the user 102 canquantize H_((q)) using an M_(q)×r_(q) semi-unitary matrix Ĝ_((q)) (whichcan be thought of as the worst-companion to Ĝ_(r), which quantizes thedirect channel). The interfering base station q, will then scheduleup-to S_(q) streams using precoding matrices that lie in a subspaceorthogonal to the span of Ĝ_((q)). The processor 210 of the user 102 canperform the following schemes to determine the PMI and the companion PMIand thereby implement step 304 of the method 300.

In accordance with one implementation, the user 102 can determine thePMIs by employing a capacity metric. For example, the user 102 canselect a matrix Ĝ_(r) for the direct channel along with theworst-companion matrices, {Ĝ_((q))}_(qεI).

$\left\{ {{\hat{G}}_{r},\left\{ {\hat{G}}_{(q)} \right\}} \right\} = {\arg \; {\max\limits_{{G \in C_{r}},{\{{G_{q} \in C_{r_{q}}}\}}_{q \in I}}\begin{Bmatrix}{{\ln {\begin{matrix}\begin{matrix}{I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} +} \\{{\rho^{\prime}H^{\dagger}{GG}^{\dagger}H} +}\end{matrix} \\{\sum\limits_{q \in I}{{\hat{\rho}}_{q}{H_{(q)}^{\dagger}\left( {I - {G_{(q)}G_{(q)}^{\dagger}}} \right)}H_{(q)}}}\end{matrix}}} -} \\{\ln {\begin{matrix}{I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} +} \\{\sum\limits_{q \in I}{{\hat{\rho}}_{q}{H_{(q)}^{\dagger}\left( {I - {G_{(q)}G_{(q)}^{\dagger}}} \right)}H_{(q)}}}\end{matrix}}}\end{Bmatrix}}}$   where$\mspace{20mu} {{\overset{\sim}{\rho} = \frac{\rho^{\prime}\left( {S - r} \right)}{M - r}},{{\hat{\rho}}_{q} = \frac{\rho_{q}^{\prime}S_{q}}{M_{q} - r_{q}}}}$

with ρ_(q)′ being the power per stream used by the q interfering basestation.

In accordance with another implementation, which can be employed in anMMSE based receiver, the processor 210 of the receiver 102 can select aPMI Ĝ_(r) for the direct channel after determining r SINRs for eachmatrix in C_(r) at step 304. Also at step 304, the receiver 102 canselect the worst-companion PMIs, {Ĝ_((q))}_(qεI). We let G=[g₁, . . . ,g_(r)].

$\begin{matrix}{{\left\{ {{\hat{G}}_{r}\left\{ {\hat{G}}_{(q)} \right\}} \right\} = {\arg \; {\max\limits_{{G \in C_{r}},{\{{G_{q} \in C_{r_{q}}}\}}_{q \in I}}\left\{ {\sum\limits_{j = 1}^{r}{\ln \left( {1 + {{SINR}_{j,r}^{MMSE}\left( {G,\left\{ {G_{q}\; \in C_{r_{q}}} \right\}_{q \in I}} \right)}} \right)}} \right\}}}}\mspace{20mu} {where}} & (22) \\{{{SINR}_{j,r}^{MMSE}\left( {G,\left\{ {G_{q} \in C_{r_{q}}} \right\}_{q \in I}} \right)} = {\rho^{\prime}g_{j}^{\dagger}{H\begin{pmatrix}\begin{matrix}{I + {\overset{\sim}{\rho}\; {H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H} +} \\{{\rho^{\prime}H^{\dagger}{\sum\limits_{k \neq j}{g_{k}g_{k}^{\dagger}H}}} +}\end{matrix} \\{\sum\limits_{q \in I}{{\hat{\rho}}_{q}{H_{(q)}^{\dagger}\left( {I - {G_{(q)}G_{(q)}^{\dagger}}} \right)}H_{(q)}}}\end{pmatrix}}^{- 1}H^{\dagger}g_{j}}} & (23)\end{matrix}$

It should be noted that the alternate rule derived in section 2.1 abovecan be extended to this scenario. Here, the user 102 first uses (12) todetermine the matrix Ĝ_(r). Next, for each qεI, the user 102 uses (12)to determine the matrix Ĝ_((q)), except the search is over C_(r) _(q)and {tilde over (V)}_((r)) is replaced by {circumflex over (V)}_((r)_(q) ₎, with {circumflex over (V)}_((r) _(q) ₎ denoting the M×r_(q)matrix formed by the r_(q) right singular vectors of H^(†) _((q)) thatcorrespond to its r_(q) largest singular values. Once {Ĝ_(r),{Ĝ_((q))}}are determined, the user 102 can compute the r SINRs corresponding to{Ĝ_(r),{Ĝ_((q))}} using (23). Alternatively, the user 102 can computethe worst-companion PMIs using the aforementioned rules. The user 102can, at step 306, then report the CQI(s) that are based on SINR(s)without the worst companions (for example using (5) with Ĝ_(r)) alongwith a delta CQI that corresponds to the average difference between theSINRs without the worst companions and those with the worst companions((23) with Ĝ_(r), {Ĝ_((q))}).

5. Signaling Schemes

As noted above, embodiments of the present principles can employ avariety of signaling schemes that convey parameter information to theuser 102. Specific examples of such signaling schemes are described indetail herein below. In particular, one or more of schemes and rulesconcerning the determination of PMIs and SINRs/CQIs described above canbe employed to implement each of the signaling schemes described hereinbelow. The operations performed in the schemes are enabled by signalingfrom the base station 104 certain parameters on a downlink(feed-forward) control channel that are then received as inputs by theuser 102. The feed back is sent by the user 102 on an uplink (feedback)control channel and is received by the base station 104. The parameterssignaled by the base-station to a user 102 are interpreted by that user102 in particular ways that are described in detail herein below.Similarly, some assumptions made by the user 102 in computing its feedback report (such as the assumed power-per-data-stream) should be knownto the base-station 104. Moreover, as described below, the feed backsent by the user 102 should permit the base station 104 to unambiguouslydetermine the portion of the feed back determined by the user viaSU-MIMO rules (in which the user assumes no other user will beco-scheduled with it) and the portion determined via MU-MIMO rules (inwhich the user accounts for the post-scheduling intra-cell interference,as discussed above).

5.1

In accordance with one implementation, the base station 104 can employsemi-static signaling to inform a user of an estimate of (or an upperbound on) the total number of streams, S, that the base station expectsto co-schedule on a sub-band. The signaling also includes a suggestedper-user MU-MIMO rank r for that user. The parameter S is cell specific(i.e., is identical for all users in a cell) whereas r is user-specific(i.e., can be different for different users in a cell).

5.1a

After receiving the signal including S and r, the user 102 can computePMIs/CQIs under MU-MIMO rules. In particular, the user 102 can determinea precoder of rank r from a codebook of rank r matrices (the precoderbeing uniquely identified by the rank r and a PMI) along withcorresponding SINRs (which are combined into one or more CQI(s)) and canreport the PMI and the CQI (s) to the base station 104. While the exactrule is an implementation-dependent, the aim of such a rule is toaccount for the post-scheduling interference using the knowledge that(up-to) S-r interfering streams may be co-scheduled. A simple rule isemployed here. In particular, suppose that the estimated channel matrixat the user terminal 102 of interest is given by H^(†)εC^(N×M) where N,Mare the number of receive and transmit antennas at the user 102 and thebase station 104, respectively. Then, in order to compute SINR(s) foreach choice of a semi-unitary M×r precoder G, the user 102 assumes thatthe interference covariance matrix is equal to

$\frac{\rho \left( {S - r} \right)}{S\left( {M - r} \right)}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H$

(up-to a scaling factor), where ρ is an estimate of the total energytransmitted per resource element. Specific rules under this assumptionwere described in detail herein above. It should be noted that thisinterference covariance matrix is derived after assuming that theinterfering streams will be scheduled along vectors that areisotropically distributed in the null space of G^(†) and then taking anexpectation over all such vectors. The assumption about the base station104 co-scheduling streams along vectors in the null space of G^(†) (ifthe user reports G as the PMI) will be closely satisfied in practice.Moreover, the isotropic assumption puts no further constraints andsimplifies computation at the user 102 by enabling the utilization ofsimple formulas. A more conservative choice is for the user to assumethe interference covariance matrix to be equal to

$\frac{\rho}{S}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H$

while computing its SINRs.

Accordingly, in one particular embodiment of method 300, the receiver212 of the user 102 can receive S and r from the base station 104 atstep 302. At step 304, the processor 210 can determine a precoder ofrank r and can compute (up-to) r SINRs assuming that there can be S-rco-scheduled interfering streams and that equal power is assigned to allS streams. Also at step 304, the processor 210 can combine the computedSINRs into one or more CQIs. Further, at step 304, the processor candenote the index identifying the precoder as an “MU-PMI” and thecomputed CQIs as “MU-CQI(s),” using, for example, corresponding tags for“MU-PMI” and “MU-CQI(s).” At step 306, the processor 210 can direct thetransmitter 212 to feedback the denoted MU-PMI and MU-CQIs to the basestation 104.

Optionally, the user 102 may also use SU-MIMO rules (i.e., rules that donot account for post-scheduling intra-cell interference) to determineanother set of CQI(s), a PMI and a rank index (RI) denoting the rank ofthe precoder indexed by this PMI. In particular, the user assumes thatno other stream intended for another user will be co-scheduled and thendetermines a precoder (which is uniquely identified by a RI and a PMI)along with the corresponding SINRs. It may then combine these SINRs intoone or more CQI(s) and report these CQI(s) and PMI,RI along with theCQI(s) and PMI determined using the MU-MIMO rules. The feed back is donein a manner that permits the base station to unambiguously determine theportion of the feed back determined via SU-MIMO rules and the portion ofthe feed back determined via MU-MIMO rules.

Optionally, the user 102 may use the precoder determined via MU-MIMOrules and may then compute additional SINRs and CQI(s) for that precoderusing SU-MIMO rules. These additional CQI(s) can then be reported alongwith the CQI(s) and PMI determined using the MU-MIMO rules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S and r from the base station 104 at step 302.At a first sub-step of step 304, the processor 210 can determine aprecoder of rank r and can compute (up-to) r SINRs assuming that therecan be S-r co-scheduled interfering streams and that equal power isassigned to all S streams. Also at the first sub-step, the processor 210can combine the computed SINRs into one or more CQIs. Further, at thefirst sub-step of step 304, the processor 210 can denote the indexidentifying the precoder as an “MU-PMI” and the computed CQIs as“MU-CQI(s),” by employing, for example, corresponding tags for “MU-PMI”and “MU-CQI(s).” At a second sub-step of step 304, using the precoderidentified by MU-PMI, the processor 210 can determine additional up-to rSINRs assuming that only r streams with equal power will be scheduledand that no interfering stream will be co-scheduled. At the secondsub-step, the processor 210 can combine the computed SINRs into one ormore CQIs and can denote these additional CQIs as “SU-CQIs” using, forexample, a corresponding tag. At step 306, the processor 210 can directthe transmitter 212 to feed-back the denoted MU-PMI and MU-CQIs alongwith the denoted SU-CQIs to the base station 104.

Optionally, the user 102 may first determine a precoder of rank r alongwith its SINRs and CQI(s) using SU-MIMO rules. It can then use theprecoder so determined to compute additional SINRs and CQI(s) for thatprecoder using MU-MIMO rules. These additional CQI(s) can then bereported along with the CQI(s) and the PMI determined using the SU-MIMOrules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S and r from the base station 104 at step 302.At a first sub-step of step 304, the processor 210 can determine aprecoder of rank r and can compute (up-to) r SINRs assuming that only rstreams with equal power will be scheduled and that no interferingstream will be co-scheduled. Also at the first sub-step, the processor210 can combine the computed SINRs into one or more CQIs and can denotethe index identifying the precoder as “SU-PMI” and the computed CQIs as“SU-CQIs” with corresponding tags. Using the precoder identified by theSU-PMI, at a second sub-step of step 304, the processor 210 candetermine additional up-to r SINRs. Here, the processor 210 assumes thatthere can be S-r co-scheduled interfering streams and that equal poweris assigned to all S streams. In addition, also at the second sub-step,the processor 210 can combine the computed SINRs into one or more CQIsand can denote these additional CQIs as MU-CQIs with one or morecorresponding tags. At step 306, the processor 210 can direct thetransmitter 212 to feed-back the denoted SU-PMI and SU-CQIs along withthe denoted along MU-CQIs to the base station 104.

5.1b

Alternatively, after receiving the signal from the base station 104, theuser 102 can first use SU-MIMO rules to determine its PMI,RI andcorresponding CQI(s) and can denote the rank of the precoder sodetermined by r′. The user 102 then determines {circumflex over(r)}=min{r′,r}. Further, the user 102 determines a PMI of rank{circumflex over (r)} and corresponding SINRs (CQI(s)) using MU-MIMOrules assuming that S-{circumflex over (r)} interfering streams may beco-scheduled. The user may then report the CQI(s) and PMI,RI determinedvia SU-MIMO rules along with the CQI(s) and PMI determined via MU-MIMOrules. As indicated above, the feed back is done in a manner thatpermits the base station 104 to unambiguously determine the portiondetermined via SU-MIMO rules and the portion determined via MU-MIMOrules. It should be noted that the rank of the SU-MIMO precoder r′ alsofixes the rank of the MU-MIMO precoder and hence the MU-MIMO PMIunambiguously determines a precoder. In another variant, only the CQI(s)and PMI determined via MU-MIMO rules may be fed-back along with the rankof the PMI {circumflex over (r)}.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S and r from the base station 104 at step 302.At a first sub-step of step 304, the processor 210 can determine a rankr′ and a precoder of rank r′. Further, at the first sub-step, theprocessor can compute (up-to) r′ SINRs, assuming that only r′ streamswith equal power will be scheduled and no interfering streams will beco-scheduled. Also at the first sub-step, the processor 210 can combinethe computed SINRs into one or more CQIs and can denote the indexidentifying the precoder as an “SU-PMI,” the r′ as an “SU-rank” and thecomputed CQIs as “SU-CQIs” using, for example, corresponding tags. At asecond sub-step of step 304, the processor 210 can determine a rankR=min(r,r′), can determine a precoder of rank R and can compute (up-to)R SINRs assuming that there can be S-R co-scheduled interfering streamsand that equal power is assigned to all S streams. Also at the secondsub-step, the processor 210 can combine the computed SINRs into one ormore CQIs and can denote the index identifying the determined precoderas “MU-PMI” and the computed CQIs as “MU-CQIs” using, for example,corresponding tags. At step 306, the processor 210 can direct thetransmitter 212 to feed back the denoted MU-PMI and MU-CQIs to thebase-station 104 along with the denoted SU-PMI, SU-rank and SU-CQIs.

Optionally, the user 102 may use a precoder, for example, AεC^(M×r′),determined via SU-MIMO rules as follows. First, the rank {circumflexover (r)}=min{r′, r} is determined and, using {circumflex over (r)}, aunique M×{circumflex over (r)} sub-matrix of A having {circumflex over(r)} columns is determined via pre-defined mapping rules that are knownin advance to all users and the base station 104 servicing the users.The user 102 then computes additional SINRs and CQI(s) for thesub-matrix so determined using MU-MIMO rules assuming that S-{circumflexover (r)} interfering streams may be co-scheduled. These additionalCQI(s) can then be reported along with the CQI(s), PMI and RI determinedusing the SU-MIMO rules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S and r from the base station 104 at step 302.At a first sub-step of step 304, the processor 210 can determine a rankr′ and a precoder of rank r′ and can compute (up-to) r′ SINRs assumingthat only r′ streams with equal power will be scheduled and nointerfering streams will be co-scheduled. Also at the first sub-step,the processor 210 can combine the computed SINRs into one or more CQIsand can denote the index identifying the precoder as an “SU-PMI,” r′ asan “SU-rank” and the computed CQIs as “SU-CQIs” using, for example,corresponding tags. At a second sub-step of step 304, the processor 210can determine a rank R=min(r,r′) and can determine a precoder of rank Rthat is a sub-matrix of the precoder identified by SU-PMI formed by asub-set of its columns. For the precoder so determined, the processor210, also at the second sub-step, can compute (up-to) R SINRs assumingthat there can be S-R co-scheduled interfering streams and that equalpower is assigned to all S streams. Further, at the second sub-step ofstep 304, the processor 210 can combine the computed SINRs into one ormore CQIs and can denote the computed CQIs as “MU-CQIs” using, forexample, a corresponding tag. At step 306, the processor 210 can directthe transmitter 212 to feed back the denoted SU-PMI, SU-rank and SU-CQIsalong with the denoted MU-CQIs to the base station 104.

It should be noted that, assuming that there can be up to S-{circumflexover (r)} co-scheduled interfering streams, the user 102 can make a moreconservative choice by determining the interference covariance matrix tobe equal to

$\frac{\rho \left( {S - \hat{r}} \right)}{S\left( {M - \hat{r}} \right)}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H$

(when examining a precoder GεC^(M×{circumflex over (r)})) whilecomputing its SINRs. In another variant, the user can instead assumethat S-r interfering streams will be co-scheduled and make a lessconservative choice in determining the interference covariance matrix tobe equal to

$\frac{\rho \left( {S - r} \right)}{\left( {S - r + \hat{r}} \right)\left( {M - \hat{r}} \right)}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}{H.}$

While the base station need not be aware of the exact rule used by theuser 102, it should be aware of the power-per-stream assumed by the userin computing its SINRs.

5.1c

It should also be noted that any user that does not receive thesemi-static signal from the base station 104 can use SU-MIMO rules todetermine its CQI(s) and PMI,RI. Such a user only reports the set ofCQI(s) and PMI,RI determined via the SU-MIMO rules. In this context, wenote that low geometry users (i.e., users whose average received signalstrength is below a threshold) are likely not suitable for MU-MIMOpairing and hence need not be semi-statically signaled by the basestation 104.

5.2

In accordance with another implementation, the base station 104 canemploy semi-static signaling to inform a user 102 of a multi-user poweroffset α. The parameter α is user-specific. The semi-static signal canoptionally include either a suggested per-user MU-MIMO rank r or amaximum per-user MU-MIMO rank r_(max), both of which can beuser-specific. Alternatively, the maximum per-user MU-MIMO rank r_(max)can be pre-determined and can be identical for all users and known tothem, in which case it need not be conveyed.

Each user 102 can estimate an energy-per-resource-element (RE) or per(RB) parameter ρ. For example, the base station 104 periodicallytransmits pilot (or reference) symbols on pre-determined positions inthe available time-frequency resources, as described in theabove-referenced commonly owned and co-pending utility applications. Thepilot symbols, as well as the positions, can be known in advance to allusers. Each user 102 can then estimate the total transmit power per REor per RB (ρ) using the signals it receives on these positions. Inaddition, in accordance with other aspects, the base station 104 canfurther control each user's estimate of ρ by signaling a user-specificparameter, for example, δ. Then, a user 102 which receives a particularvalue of δ can multiply its estimated ρ by δ and can employ δρ as thetotal transmit power ρ per RE or per RB. It should also be noted that,in the implementations described herein above and below, ρ can morebroadly be considered to be a constant that is proportional to themaximum bound of the sum power constraint per RE or per RB.

Using the estimated ρ with α, in order to determine a precoder andcompute its SINRs under MU-MIMO rules, the user 102 assumes that on eachresource element or resource block on which it will be scheduled, afraction of the energy or power ρα will be used for its desired signalwhereas the remaining (1−α)ρ will be used for the interferers.

5.2a

After receiving the semi-static multi-user power offset parameter α, theuser 102 computes PMI,CQI(s) and possibly a rank under MU-MIMO rulesbased on the parameter α. In particular, in order to compute SINR(s) foreach choice of a semi-unitary M×r precoder G, the user assumes that theinterference covariance matrix is equal to

$\frac{\rho \left( {1 - \alpha} \right)}{M - r}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}H$

and that each of its r desired streams corresponding to the r columns ofG are sent with power

$\frac{\alpha\rho}{r}.$

Note that a value of rank r can also be semi-statically signaled to auser 102 from the base station 104, in which case the user 102 onlyreports the PMI and CQI(s). Alternatively, the user 102 can itselfoptimize and choose a value of r (subject to it being no greater thanr_(max)) in which case the user reports the rank along with the PMI andCQI(s).

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive α, ρ and r from the base station 104 at step302. At step 304, the processor 210 determines a precoder of rank r andcomputes (up-to) r SINRs. Here, the processor 210 assumes αρ to be thesum power assigned to the r streams intended for the user 102 andassumes (1−α)ρ to be the sum power assigned to the interfering streamsco-scheduled with the streams intended for the user 102. Also at step304, the processor 210 combines the computed SINRs into one or more CQIsand denotes the index identifying the precoder as an “MU-PMI” and thecomputed CQIs as “MU-CQIs,” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-PMI and the denoted MU-CQIs to the base station 104.

Optionally, the user 102 may also use SU-MIMO rules to determine anotherset of CQI(s) and a PMI,RI. It may then report these CQI(s) and PMI,RIalong with the CQI(s) and PMI, and possibly a corresponding rank,determined using the MU-MIMO rules. The feed back is done in a mannerthat permits the base station to unambiguously determine the portion ofthe feed back determined via SU-MIMO rules and the portion determinedvia MU-MIMO rules.

Optionally, such a user may use the precoder determined via MU-MIMOrules and then compute additional SINRs and CQI(s) for that precoderusing SU-MIMO rules. These additional CQI(s) can then be reported alongwith the CQI(s) and PMI possibly rank determined using the MU-MIMOrules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive α, ρ and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines aprecoder of rank r and computes (up-to) r SINRs. Here, the processor 210assumes αρ to be the sum power assigned to the r streams intended forthe user 102 and assumes (1−α)ρ to be the sum power assigned to theinterfering streams co-scheduled with the streams intended for the user102. Also at the first sub-step, the process 210 combines the computedSINRs into one or more CQIs and denotes the index identifying theprecoder as an “MU-PMI” and the computed CQIs as “MU-CQIs,” using, forexample, corresponding tags. At a second sub-step of step 304, theprocessor 210 uses the precoder identified by the MU-PMI to determineadditional up-to r SINRs. Here, the processor 210 assumes that only rstreams with equal power will be scheduled and no interfering streamwill be co-scheduled. Also at the second sub-step, the processor 210combines the computed SINRs into one or more CQIs and denotes theseadditional CQIs as “SU-CQIs” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-PMI and MU-CQIs to the base station 104 along with thedenoted SU-CQIs.

Optionally, the user 102 may also use SU-MIMO rules to determine a setof CQI(s) and PMI and RI. The RI is determined if no rank is signaledfrom the base station 104. Further, the rank can be constrained to be nogreater than r_(max). The user 102 can then use the precoder sodetermined to compute additional SINRs and CQI(s) for that precoderusing MU-MIMO rules. These additional CQI(s) can then be reported alongwith the CQI(s), PMI and (possibly) a precoder rank determined using theSU-MIMO rules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive α, ρ and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines aprecoder of rank r and computes (up-to) r SINRs assuming that only rstreams with equal power will be scheduled and no interfering streamwill be co-scheduled. In addition, at the first sub-step, the processor210 combines the computed SINRs into one or more CQIs and denotes theindex identifying the precoder as an “SU-PMI” and the computed CQIs as“SU-CQIs” using, for example, corresponding tags. At a second sub-stepof step 304, the processor 210 employs the precoder identified by theSU-PMI to determine additional up-to r SINRs assuming that αβ is thepower assigned to r streams intended for the user 102 and that (1−α)ρ isthe power assigned to the co-scheduled interfering streams. Also at thesecond sub-step, the processor 210 combines computed SINRs into one ormore CQIs and denotes these additional CQIs as “MU-CQIs” usingcorresponding tags. At step 306, the processor 210 directs thetransmitter to feed back the denoted SU-PMI and the denoted SU-CQIs tothe base-station along with the denoted MU-CQIs

5.2b

Alternatively, in accordance with another implementation, afterreceiving the signal from the base station 104, the user 102 first usesSU-MIMO rules to determine its PMI,RI and corresponding CQI(s). Wedenote the rank of the precoder so determined by r′. The user 102 thendetermines F=min{r′,r} if the per-user MU-MIMO rank r is conveyed by thebase station 104. Otherwise, the user determines F=min{r′,r_(max)}. Theuser 102 may then determine a PMI of rank {circumflex over (r)} andcorresponding SINRs/CQI(s) using MU-MIMO rules. In accordance with theseMU-MIMO rules (when examining a precoder GεC^(M×{circumflex over (r)})),the interference covariance matrix is assumed to be equal to

$\frac{\rho \left( {1 - \alpha} \right)}{M - \hat{r}}{H^{\dagger}\left( {I - {GG}^{\dagger}} \right)}{H.}$

The user 102 further assumes that each of the {circumflex over (r)}streams directed to the user 102 and corresponding to the {circumflexover (r)} columns of G are sent with power αρ/{circumflex over (r)}. Theuser 102 may then report the CQI(s) and PMI,RI determined via SU-MIMOrules along with the CQI(s) and PMI determined via MU-MIMO rules. Thefeed back from the user 102 is performed in a manner that permits thebase station to unambiguously determine the portion of the feed backdetermined via SU-MIMO rules and the portion of the feed back determinedvia MUMIMO rules. It should be noted that the rank of the SU-MIMOprecoder r′ also fixes the rank of the MU-MIMO precoder and hence theMU-MIMO PMI unambiguously determines a precoder. In another variant,only the CQI(s) and PMI determined via MU-MIMO rules may be fed backalong with the rank of the PMI {circumflex over (r)}.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive α, ρ and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines arank r′ and a precoder of rank r′. The processor 210 also computes(up-to) r′ SINRs assuming that only r′ streams with equal power will bescheduled and no interfering streams will be co-scheduled. In addition,the processor 210 at the first sub-step combines the computed SINRs intoone or more CQIs and denotes the index identifying the precoder as an“SU-PMI,” the r′ as an “SU-rank” and the computed CQIs as “SU-CQIs”using, for example, corresponding tags. At a second sub-step of step304, the processor 210 determines a rank R=min(r,r′) and determines aprecoder of rank R. Further, at the second sub-step, the processor 210computes (up-to) R SINRs assuming that αρ is the sum power assigned tothe R streams directed to the user 102 and that (1−α)ρ is the sum powerassigned to the co-scheduled interfering streams. In addition, theprocessor combines computed SINRs into one or more CQIs and denotes theindex identifying the determined precoder as an “MU-PMI” and thecomputed CQIs as “MU-CQIs” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-PMI and MU-CQIs to the base station 104 along with thedenoted SU-PMI, SU-rank and SU-CQIs.

Optionally, the user 102 may use the precoder, say AεC^(M×r′),determined via SU-MIMO rules as follows. First the rank {circumflex over(r)}=min{r′, r} (or {circumflex over (r)}=min{r′, r′, r_(max)}) isdetermined and, using it, a unique M×{circumflex over (r)} sub-matrix ofA having {circumflex over (r)} columns is determined via pre-definedmapping rules that are known in advance to the base station 104 and allusers served by the base station. The sub-matrix is denoted by B. Theuser 102 then computes additional SINRs and CQI(s) using MU-MIMO rulesassuming that the interference covariance matrix is equal to

$\frac{\rho \left( {1 - \alpha} \right)}{M - \hat{r}}{H^{\dagger}\left( {I - {BB}^{\dagger}} \right)}H$

and that each of the {circumflex over (r)} streams directed to the user102 and corresponding to the {circumflex over (r)} columns of B are sentwith power αρ/{circumflex over (r)}. The user 102 can then report theseadditional CQI(s) along with the CQI(s) and PMI and RI determined usingthe SU-MIMO rules to the base station 104.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive α, ρ and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines arank r′, a precoder of rank r′ and computes (up-to) r′ SINRs assumingthat only r′ streams with equal power will be scheduled and nointerfering streams will be co-scheduled. Also at the first sub-step,the processor 210 combines the computed SINRs into one or more CQIs anddenotes the index identifying the precoder as an “SU-PMI,” denotes therank r′ as an “SU-rank” and denotes the computed CQIs as “SU-CQIs” usingfor example, corresponding tags. At a second sub-step of step 304, theprocessor 210 determines a rank R=min(r,r′) and determines a precoder ofrank R that is a sub-matrix of the precoder identified by the SU-PMI andis formed by a sub-set of the columns of the precoder identified by theSU-PMI. For the precoder of rank R so determined, the processor 210computes (up-to) R SINRs assuming that αρ is the sum power assigned tothe R streams directed to the user 102 and that (1−α)ρ is the sum powerassigned to the co-scheduled interfering streams. Also at the secondsub-step, the processor 210 combines the computed SINRs into one or moreCQIs and denotes the computed CQIs as “MU-CQIs” using, for example,corresponding tags. At step 306, the processor 210 directs thetransmitter 212 to feed back the denoted SU-rank, SU-PMI and SU-CQIs tothe base station 104 along with the denoted MU-CQIs.

52c

It should be noted that any user that does not receive the semi-staticsignal from the base station uses the SU-MIMO rules to determine itsCQI(s) and PMI,RI. Such a user only reports the set of CQI(s) and PMI,RIdetermined via the SU-MIMO rules. In this context, we note that lowgeometry users (i.e., users whose average received signal strength isbelow a threshold) are likely not suitable for MU-MIMO pairing and henceneed not be semi-statically signaled by the base station 104.

It should also be noted that in all cases when feeding back bothSU-CQI(s) and MU-CQI(s), the user 102 can exploit differential feed backto reduce the feed back overhead. For example, the user 102 can feedback an MU-CQI (SU-CQI) along with a differential CQI such that the sum(difference) of the MU-CQI (SU-CQI) and the differential CQI yields acorresponding SU-CQI (MU-CQI).

Furthermore, in order to maximize scheduling gain, complete SU feed back(PMI,RI and CQI(s)) computed under SU-MIMO rules and MU-feed back (PMI,CQI(s) and possibly rank) computed under MU-MIMO rules should bepermitted. However, this would impose a very high feed back burden.Thus, several options that seek to achieve the ideal schedulingperformance but with reduced feed back overhead have been describedabove. For example, as noted above, the complete SU-feed back can beprovided with reduced MU-feed back. This is made possible by forcing theMU-rank F to be equal to min{r′,r} (or F=min{r′,r_(max)}) where r′ isthe computed SU-rank. This is sensible, as r′ is the optimal rank thatthe user 102 deems it can support in the absence of intra-cellinterference from co-scheduled streams. Thus, the rank in the presenceof possible intra-cell interference should not exceed it. To furtherreduce feed back overhead, as indicated above, the MU-precoder can be aunique sub-matrix of the SU-precoder (i.e., the precoder determinedunder SU-MIMO rules). This will lead to a negligible performancedegradation when r′≦r (or r′≦r_(max)), as the SU-precoder will be areasonably good choice because it approximates the first r′ dominantright singular vectors of H^(†). Along similar lines, only one set ofcomplete MU feed back can be sent accompanied by additional CQI(s)computed under SU-MIMO rules for the MU-precoder, as described above.

It should further be noted that other embodiments of method 300 can beemployed using aspects described above. For example, in one suchembodiment of method 300, the receiver 212 of the user 102 can receiveα, ρ and r_(max) from the base station 104 at step 302. At step 304, theprocessor 210 determines a rank r (no greater than r_(max)) and aprecoder of rank r. In addition, the processor 210 computes (up-to) rSINRs assuming that αρ is the sum power assigned to r streams directedto the user 102 and that (1−α)ρ is the sum power assigned to theco-scheduled interfering streams. Further, also at step 304, theprocessor 210 combines the computed SINRs into one or more CQIs anddenotes the index identifying the precoder as an “MU-PMI,” denotes therank r as an “MU-rank” and denotes the computed CQIs as “MU-CQIs” using,for example, corresponding tags. At step 306, the processor 210 directsthe transmitter 212 to feed back the denoted the denoted MU-rank, MU-PMIand MU-CQIs to the base station 104.

In another embodiment of method 300, the receiver 212 of the user 102can receive α, ρ and r_(max) from the base station 104 at step 302. At afirst sub-step of step 304, the processor 210 determines a rank r (nogreater than r_(max)) and a precoder of rank r. In addition, theprocessor 210 computes (up-to) r SINRs assuming that αρ is the sum powerassigned to the r streams directed to the user 102 and that (1−α)ρ isthe sum power assigned to the co-scheduled interfering streams. Also atthe first sub-step, the processor 210 combines the computed SINRs intoone or more CQIs and denotes the index identifying the precoder as an“MU-PMI,” denotes the rank r as an “MU-rank” and denotes the computedCQIs as “MU-CQIs” using, for example, corresponding tags. At a secondsub-step of step 304, the processor 210 uses the precoder identified bythe MU-PMI to determine additional up-to r SINRs assuming that only rstreams with equal power will be scheduled and no interfering streamwill be co-scheduled. Also at the second sub-step, the processor 210combines the computed SINRs into one or more CQIs and denotes theseadditional CQIs as “SU-CQIs” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-rank, MU-PMI and MU-CQIs to the base station 104 along withthe denoted SU-CQIs.

In an alternative embodiment of method 300, the receiver 212 of the user102 can receive α, ρ and r_(max) from the base station 104 at step 302.At a first sub-step of step 304, the processor 210 determines a precoderof rank r (no greater than r_(max)) and computes (up-to) r SINRsassuming that only r streams with equal power will be scheduled and nointerfering stream will be co-scheduled. Also at the first sub-step, theprocessor 210 combines the computed SINRs into one or more CQIs anddenotes the index identifying the precoder as an “SU-PMI,” the rank r asan “SU-rank” and the computed CQIs as “SU-CQIs” using, for example,corresponding tags. At a second sub-step of step 304, the processor 210uses the precoder identified by the SU-PMI to determine additional up-tor SINRs assuming that αρ is the power assigned to the r streams directedto the user 102 and that (1−α)ρ is the power assigned to theco-scheduled interfering streams. Also at the second sub-step, theprocessor 210 combines the computed SINRs into one or more CQIs anddenotes these additional CQIs as “MU-CQIs” using, for example,corresponding tags. At step 306, the processor 210 directs thetransmitter 212 to feed back the denoted SU-rank, SU-PMI and SU-CQIs tothe base station 104 along with the denoted MU-CQIs.

6. Additional Signaling Schemes

In the signaling schemes described above, the base station 104 and theuser 102 can communicate various parameters to enable the base station104 to determine scheduling parameters based on a relatively accurateestimate of channel conditions. It should be noted that other parametersand/or combinations of parameters can be communicated between the basestation 104 and the user 102 to improve the accuracy of the CQIs andPMIs determined in the system. In particular, the fraction α of thetotal transmit power that will be used for a user's desired signal, thetotal number of streams S and an estimate (r) of or an upper bound on(r_(max)) a suggested rank can be signaled from the base station 104 tothe user 102 to permit the user 102 to determine the PMI and/or CQIsusing the equations described in detail above. The parameters signaledby the base-station to a user 102 are interpreted by that user 102 inparticular ways that are described in detail herein below. Similarly,some assumptions made by the user 102 in computing its feed back report(such as the assumed power-per-data-stream) should be known to thebase-station 104. Moreover, as described below, the feed back sent bythe user 102 should permit the base station 104 to unambiguouslydetermine the portion of the feed back determined by the user viaSU-MIMO rules and the portion of the feed back determined via MU-MIMOrules.

6.1

In accordance with one implementation, the base station 104 can employfeed-forward signaling to inform a user 102 of an estimate of or anupper bound on the total number of streams, S, that the base stationexpects to co-schedule on one or more sub-bands. The signaling can alsoinclude a suggested per-user MU-MIMO rank r. In addition, the signalingcan further include a multi-user power offset α. Moreover, each user 102can estimate an energy-per-resource-element or per-resource-blockparameter ρ. While computing its SINRs, the user 102 uses ρ as anestimate of the total transmit power that the base station 104 willapply on a time-frequency resource element or block. For example, theuser 102 can estimate ρ as described above.

6.1a

After receiving the signal from the base station 104, the user 102 cancompute the PMI/CQI under MU-MIMO rules. In particular, the user 102 candetermine a precoder of rank-r (that is no greater than 5) from acodebook of rank-r matrices, where the precoder is uniquely identifiedby the rank r, and a PMI, along with corresponding SINRs, which arecombined into one or more CQI(s). The user 102 can report the PMI andthe CQI(s) to the base station 104. While the exact rule is animplementation matter, the aim of such a rule is to account for thepost-scheduling interference using the knowledge that (up-to) S-rinterfering streams may be co-scheduled. Such a rule can also assumethat a fraction α of the transmit power ρ will be used for the r streamsdirected to the user 102 that are transmitted along the r columns of theprecoder being examined, whereas the remaining part (1−α)ρ will be usedto transmit the S-r co-scheduled interfering streams. In particular, foreach choice of a semi-unitary M×r precoder G, the user can assume thatthe desired r streams (transmitted along the r columns of G) will sharethe fraction α of the transmit power equally, whereas the interferingS-r streams (transmitted along vectors that are mutually orthogonal andlie in the null space of G^(†)) will share the remaining fraction 1−α ofthe transmit power equally. It should be noted that the case α<1 and S=rshould either be avoided or, in this case, the user 102 can ignore α andinstead assume α=1 or some pre-determined value, which implies thatthere is no need to signal α for S=r.

Accordingly, in one embodiment of method 300, the receiver 212 of theuser 102 can receive S, α, and r from the base station 104 at step 302.At step 304, the processor 210 determines a precoder of rank r andcomputes (up-to) r SINRs assuming that the fraction α of the transmitpower is assigned to the r streams directed to the user 102 and that theremaining fraction (1−α) of the transmit power is assigned to theco-scheduled S-r interfering streams. In addition, also at step 304, theprocessor 210 combines the computed SINRs into one or more CQIs anddenotes the index identifying the precoder as an “MU-PMI” and thecomputed CQIs as “MU-CQIs” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-PMI and MU-CQIs to the base station 104.

Optionally, the user 102 may also use SU-MIMO rules to determine anotherset of CQI(s) and PMI and rank index (RI). Here, the user 102 assumesthat all the transmit power will be shared equally among the desiredstreams. Further, the user 102 assumes that no other stream intended foranother user will be co-scheduled. The user 102 also determines aprecoder (which is uniquely identified by an RI and a PMI) along withthe corresponding SINRs. The user 102 may then combine these SINRs intoone or more CQI(s) and report these CQI(s) and PMI,RI along with theCQI(s) and PMI determined using the MU-MIMO rules. The feed back is donein a manner that permits the base station 104 to unambiguously determinethe portion of the feed back determined via SU-MIMO rules and theportion of the feed back determined via MU-MIMO rules.

Optionally, the user 102 may use the precoder determined via MU-MIMOrules and may then compute additional SINRs and CQI(s) for that precoderusing SU-MIMO rules. These additional CQI(s) can then be reported alongwith the CQI(s) and PMI determined using the MU-MIMO rules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines aprecoder of rank r and computes (up-to) r SINRs assuming that thefraction α of the transmit power is assigned to the r streams directedto the user 102 and that the remaining fraction (1−α) of the transmitpower is assigned to the co-scheduled S-r interfering streams. Inaddition, the processor 210 combines computed SINRs into one or moreCQIs and denotes the index identifying the precoder as an “MU-PMI” andthe computed CQIs as “MU-CQIs” using, for example corresponding tags. Ata second sub-step of step 304, the processor 210 employs the precoderidentified by the MU-PMI to determine additional up-to r SINRs assumingthat only r streams with equal power will be scheduled and that nointerfering stream will be co-scheduled. Further, the processor 210combines the computed SINRs into one or more CQIs and denotes theseadditional CQIs as “SU-CQIs” using, for example, corresponding tags. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted MU-PMI and MU-CQIs to the base station 104 along with thedenoted SU-CQIs.

Optionally, the user 102 may first determine a precoder of rank r alongwith its SINRs and CQI(s) using SU-MIMO rules. The user 102 can then usethe precoder so determined and can compute additional SINRs and CQI(s)for that precoder using MU-MIMO rules. These additional CQI(s) can thenbe reported along with the CQI(s) and PMI determined using the SU-MIMOrules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines aprecoder of rank r and computes (up-to) r SINRs assuming that only rstreams with equal power will be scheduled and that no interferingstream will be co-scheduled. The processor 210 combines computed SINRsinto one or more CQIs and denotes the index identifying the precoder asan “SU-PMI” and the computed CQIs as “SU-CQIs” using, for example,corresponding tags. At a second sub-step of step 304, the processor 210employs the precoder identified by the SU-PMI and determines additionalup-to r SINRs assuming that the fraction α of the transmit power isassigned to the r streams directed to the user 102 and that theremaining fraction (1−α) of the transmit power is assigned to theco-scheduled S-r interfering streams. The user 102 also combinescomputed SINRs into one or more CQIs and denotes these additional CQIsas “MU-CQIs” using, for example corresponding tags. At step 306, theprocessor 210 directs the transmitter 212 to feed back the denotedSU-PMI and SU-CQIs to the base station 104 along with the denotedMU-CQIs.

6.1b

Alternatively, after receiving the signal from the base station 104, theuser 102 first uses SU-MIMO rules to determine its PMI,RI andcorresponding CQI(s). The rank of the precoder so determined is denotedby r′. The user 102 then determines {circumflex over (r)}=min{r′,r}.Further, the user 102 determines a PMI identifying a (MU-) precoder ofrank {circumflex over (r)} and determines corresponding SINRs (CQI(s))using MU-MIMO rules assuming that S-{circumflex over (r)} interferingstreams may be co-scheduled and that a fraction α of the transmit powerwill be shared equally among the desired {circumflex over (r)} streams(transmitted along the columns of the reported MU-precoder) and theremaining fraction 1−α of the transmit power will be shared equallyamong the co-scheduled S-{circumflex over (r)} streams. TheS-{circumflex over (r)} streams are, in turn, transmitted along mutuallyorthogonal vectors that are also orthogonal to the columns of thereported MU-precoder. The user 102 may then report the CQI(s) and PMI,RIdetermined via SU-MIMO rules along with the CQI(s) and PMI determinedvia MU-MIMO rules. The feed back is done in a manner that permits thebase station 104 to unambiguously determine the portion of the feed backdetermined via SU-MIMO rules and the portion of the feed back determinedvia MU-MIMO rules. It should be noted that the rank of the SU-MIMOprecoder r′ also fixes the rank of the MU-MIMO precoder and hence theMU-MIMO PMI unambiguously determines a precoder. In another variant,only the CQI(s) and PMI determined via MU-MIMO rules may be fed backalong with the rank of the PMI {circumflex over (r)}.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines arank r′, a precoder of rank r′ and computes (up-to) r′ SINRs assumingthat only r′ streams with equal power will be scheduled and that nointerfering streams will be co-scheduled. The processor 210 alsocombines computed SINRs into one or more CQIs and denotes the indexidentifying the precoder as an “SU-PMI,” denotes the rank r′ as an“SU-rank” and denotes the computed CQIs as “SU-CQIs” using, for example,corresponding tags. At a second sub-step of step 304, the processor 210determines a rank R=min(r,r′) and determines a precoder of rank R. Theprocessor 210 further computes (up-to) R SINRs assuming that thefraction α of the transmit power is assigned to the R streams directedto the user 102 and that the remaining fraction (1−α) of the transmitpower is assigned to the co-scheduled S-R interfering streams. Also atthe second sub-step, the processor 210 combines the computed SINRs intoone or more CQIs and denotes the index identifying the determinedprecoder as an “MU-PMI” and the computed CQIs as “MU-CQIs” using, forexample, corresponding tags. At step 306, the processor 210 directs thetransmitter 212 to feed back the denoted MU-PMI and MU-CQIs to the basestation 104 along with the denoted SU-PMI, SU-rank and SU-CQIs.

Optionally, such the user 102 may use the precoder, for example,AεC^(M×r′), determined via SU-MIMO rules as follows. First, the user 102determines the rank {circumflex over (r)}=min{r′, r}. Using the rank{circumflex over (r)}, the user 102 determines an MU-precoder as aunique M×{circumflex over (r)} sub-matrix of A having {circumflex over(r)} columns. The sub-matrix is determined via pre-defined mapping rulesthat are known in advance to all users and the base station 104 servingthe users. The user 102 then computes additional SINRs and CQI(s) forthe sub-matrix so determined using MU-MIMO rules assuming thatS-{circumflex over (r)} interfering streams may be co-scheduled and thata fraction α of the transmit power will be shared equally among the{circumflex over (r)} streams (transmitted along the columns of thedetermined MU-precoder) directed to the user and that the remainingfraction 1−α of the transmit power will be shared equally among theco-scheduled S-{circumflex over (r)} streams. The S-{circumflex over(r)} stream are transmitted along mutually orthogonal vectors that arealso orthogonal to the columns of the MU-precoder. The user 102 canreport these additional CQI(s) along with the CQI(s), PMI and RIdetermined using the SU-MIMO rules.

Here, it is noted that, in another variant, the user 102 can insteadassume that the remaining fraction 1−α of the transmit power will beshared equally among S-r co-scheduled streams which are transmittedalong mutually orthogonal vectors that are also orthogonal to thecolumns of the MU-precoder. While the base station 104 need not be awareof the exact rule used by the user, it should be aware of the fractionof the power the user assumes for each of its desired streams whilecomputing its SINRs.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r from the base station 104 at step302. At a first sub-step of step 304, the processor 210 determines arank r′ and a precoder of rank r′. The processor 210 also computes(up-to) r′ SINRs assuming that only r′ streams with equal power will bescheduled and that no interfering streams will be co-scheduled. Also atthe first sub-step, the processor 210 combines the computed SINRs intoone or more CQIs and denotes the index identifying the precoder as an“SU-PMI,” the rank r′ as an “SU-rank” and the computed CQIs as “SU-CQIs”using, for example, corresponding tags. At a second sub-step of step304, the processor 210 determines a rank R=min(r,r′) and determines aprecoder of rank R that is a sub-matrix of the precoder identified bythe SU-PMI is formed by a sub-set of the SU-precoder columns. For theprecoder of rank R so determined, the processor 210 computes (up-to) RSINRs assuming that the fraction α of the transmit power is assigned tothe R streams directed to the user 102 and that the remaining fraction(1−α) of the transmit power is assigned to the co-scheduled S-Rinterfering streams. Also at the second sub-step, the processor 210combines the computed SINRs into one or more CQIs and denotes thecomputed CQIs as “MU-CQIs” using, for example, a corresponding tag. Atstep 306, the processor 210 directs the transmitter 212 to feed back thedenoted SU-rank, SU-PMI and SU-CQIs to the base station 104 along withthe denoted MU-CQIs.

6.1c

Any user that does not receive the semi-static signal from the basestation 104 uses SU-MIMO rules to determine its CQI(s) and PMI,RI. Sucha user only reports the set of CQI(s) and PMI,RI determined via theSU-MIMO rules. In this context, it is noted that low geometry users(i.e., users whose average received signal strength is below athreshold) are likely not suitable for MU-MIMO pairing and hence neednot be semi-statically signaled by the base station 104.

6.2

In accordance with another implementation, the base station 104 canemploy feed-forward signaling to inform a user 102 about an estimate of(or an upper bound on) the total number of streams, S, that the basestation 104 expects to co-schedule on at least one sub-band. Thesignaling can also include a maximum per-user MU-MIMO rank r_(max). Inaddition, the signaling can include a multi-user power offset α. Eachuser 102 can estimate an energy-per-resource-element or block parameterρ. While computing its SINRs, the user 102 uses ρ as an estimate of thetotal transmit power that the base station 104 will apply on atime-frequency resource element or block.

6.2a

After receiving the signal from the base station 104, the user 102computes RI, PMI/CQI under MU-MIMO rules. In particular, the user 102can determine a precoder of rank {tilde over (r)} (that is no greaterthan r_(max)) from a codebook of rank-{tilde over (r)} matrices (theprecoder being uniquely identified by the rank {tilde over (r)} and aPMI) along with corresponding SINRs (which are combined into one or moreCQI(s)). Further, the user 102 can report the rank {tilde over (r)}, thePMI and the CQI (s) to the base station 104. While the exact rule is animplementation matter, the aim of such a rule is to account for thepost-scheduling interference using the knowledge that (up-to) S-{tildeover (r)} interfering streams may be co-scheduled. Such a rule can alsoassume that a fraction α of the transmit power ρ will be used for the{tilde over (r)} streams directed to the user 102 that are transmittedalong the {tilde over (r)} columns of the precoder being examined,whereas the remaining part (1−α)ρ will be used to transmit theS-{circumflex over (r)} co-scheduled interfering streams. In particular,for each choice of a semi-unitary M×{tilde over (r)} precoder G, theuser 102 can assume that the desired {tilde over (r)} streams(transmitted along the r columns of G) will share the fraction α of thetransmit power equally, whereas the interfering S-{tilde over (r)}streams (transmitted along vectors that are mutually orthogonal and liein the null space of G^(†)) will share the remaining fraction 1−α of thetransmit power equally. The setting S≦r_(max) should either be avoidedor, in this case, the user 102 can assume r_(max)=S. Moreover, inevaluating a precoder of rank equal to S (which is possible whenr_(max)=S), the user 102 can instead assume α=1 or some pre-determinedvalue. For most rules, the user will then report a precoder of rank S sothat the system can choose to configure the user to not report or feedback a rank in this case. Here, the rank will be assumed to be S.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r_(max) from the base station 104 atstep 302. At step 304, the processor 210 determines a rank r (no greaterthan r_(max)) and a precoder of rank r. Further, the processor 210computes (up-to) r SINRs assuming that the fraction α of the transmitpower is assigned to the r streams directed to the user 102 and that theremaining fraction (1−α) of the transmit power is assigned to theco-scheduled S-r interfering streams. In addition, the processor 210combines computed SINRs into one or more CQIs and denotes the indexidentifying the precoder as an “MU-PMI,” denotes the rank r as an“MU-rank” and denotes the computed CQIs as “MU-CQIs” using, for example,corresponding tags. At step 306, the processor 210 directs thetransmitter 212 to feed back the denoted MU-rank, MU-PMI and MU-CQIs tothe base station 104 along with the denoted SU-CQIs.

Optionally, the user 102 may also use SU-MIMO rules to determine anotherset of CQI(s), a PMI and a rank index (RI). In particular, the user 102assumes that no other stream intended for another user will beco-scheduled and then determines a precoder (which is uniquelyidentified by an RI and a PMI) along with the corresponding SINRs. Theuser 102 may then combine these SINRs into one or more CQI(s) and mayreport these CQI(s) and PMI,RI along with the CQI(s) and PMI, RIdetermined using the MU-MIMO rules. The feed back is done in a mannerthat permits the base station to unambiguously determine the portion ofthe feed back determined via SU-MIMO rules and the portion of the feedback determined via MU-MIMO rules.

Optionally, the user 102 may use the precoder determined via MU-MIMOrules and may then compute additional SINRs and CQI(s) for that precoderusing SU-MIMO rules. The user 102 can then report these additionalCQI(s) along with the CQI(s) and PMI, RI determined using the MU-MIMOrules.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r_(max) from the base station 104 atstep 302. At a first sub-step of step 304, the processor 210 determinesa rank r (no greater than r_(max)) and a precoder of rank r. Inaddition, the processor 210 computes (up-to) r SINRs assuming that thefraction α of the transmit power is assigned to the r streams directedto the user 102 and that the remaining fraction (1−α) of the transmitpower is assigned to the co-scheduled S-r interfering streams. Further,the processor 210 combines computed SINRs into one or more CQIs anddenotes the index identifying the precoder as an “MU-PMI,” denotes therank r as an “MU-rank” and the computed CQIs as “MU-CQIs” using, forexample, corresponding tags. At a second sub-step of step 304, theprocessor 210 employs the precoder identified by the MU-PMI to determineadditional up-to r SINRs assuming that only r streams with equal powerwill be scheduled and that no interfering stream will be co-scheduled.Also at the second sub-step, the processor 210 combines the computedSINRs into one or more CQIs and denotes these additional CQIs as“SU-CQIs” using, for example, a corresponding tag. At step 306, theprocessor 210 directs the transmitter 212 to feed back the denotedMU-rank, MU-PMI and MU-CQIs to the base station 104 along with thedenoted SU-CQIs.

Optionally, the user 102 may first determine a precoder of rank {tildeover (r)} (that is no greater than r_(max)) along with its SINRs andCQI(s) using SU-MIMO rules. It can then use the precoder so determinedand can compute additional SINRs and CQI(s) for that precoder usingMU-MIMO rules. The user 102 can report these additional CQI(s) alongwith the CQI(s) and PMI, RI determined using the SU-MIMO rules to thebase station 104.

Accordingly, in another embodiment of method 300, the receiver 212 ofthe user 102 can receive S, α, and r_(max) from the base station 104 atstep 302. At a first sub-step of step 304, the processor 210 determinesa precoder of rank r (no greater than r_(max)) and computes (up-to) rSINRs assuming that only r streams with equal power will be scheduledand that no interfering stream will be co-scheduled. Also at the firstsub-step, the processor 210 combines the computed SINRs into one or moreCQIs and denotes the index identifying the precoder as an “SU-PMI,”denotes the rank r as an “SU-rank” and denotes the computed CQIs as“SU-CQIs” using, for example corresponding tags. At a second sub-step ofstep 304, the processor 210 employs the precoder identified by theSU-PMI to determine additional up-to r SINRs assuming that the fractionα of the transmit power is assigned to the r streams directed to theuser 102 and that the remaining fraction (1−α) of the transmit power isassigned to the co-scheduled S-r interfering streams. In addition, theprocessor 210 combines the computed SINRs into one or more CQIs anddenotes these additional CQIs as “MU-CQIs” using, for example, acorresponding tag. At step 306, the processor 210 directs thetransmitter 212 to feed back the denoted SU-rank, SU-PMI and SU-CQIs tothe base station 104 along with the denoted MU-CQIs

6.2b

Alternatively, after receiving the signal from the base station 104, theuser 102 first uses SU-MIMO rules to determine its PMI,RI andcorresponding CQI(s). The rank of the precoder so determined is denotedby r′. The user 102 then determines {circumflex over(r)}=min{r′,r_(max))}. Further, the user 102 determines a PMIidentifying a (MU-) precoder of rank {circumflex over (r)} andcorresponding SINRs (CQI(s)) using MU-MIMO rules assuming thatS-{circumflex over (r)} interfering streams may be co-scheduled and thata fraction α of the transmit power will be shared equally among thedesired {circumflex over (r)} streams (transmitted along the columns ofthe reported MU-precoder) directed to the user 102 and that theremaining fraction 1−α of the transmit power will be shared equallyamong the co-scheduled S-{circumflex over (r)} streams. TheS-{circumflex over (r)} streams are transmitted along mutuallyorthogonal vectors that are also orthogonal to the columns of thereported MU-precoder. The user 102 may then report the CQI(s) and PMI,RIdetermined via SU-MIMO rules along with the CQI(s) and PMI determinedvia MU-MIMO rules to the base station 104. The feed back is done in amanner that permits the base station 104 to unambiguously determine theportion of the feed back determined via SU-MIMO rules and the portion ofthe feed back determined via MU-MIMO rules. It should be noted that therank of the SU-MIMO precoder r′ also fixes the rank of the MU-MIMOprecoder and hence the MU-MIMO PMI unambiguously determines a precoder.In another variant, the user 102 only feeds back the CQI(s) and PMIdetermined via MU-MIMO rules along with the rank {circumflex over (r)}of the PMI.

Optionally, the user 102 may use the precoder, for example, AεC^(M×r′),determined via SU-MIMO rules as follows. First, the user 102 determinesthe rank {circumflex over (r)}=min {r′, r_(max)}. The user 102 uses therank F to determine an MU-precoder that is a unique M×{circumflex over(r)} sub-matrix of A having {circumflex over (r)} columns. Thesub-matrix is determined via pre-defined mapping rules that are known inadvance to all users and the base-station 104 serving the users. Theuser 102 then computes additional SINRs and CQI(s) for the sub-matrix sodetermined using MU-MIMO rules assuming that S-{circumflex over (r)}interfering streams may be co-scheduled and that a fraction α of thetransmit power will be shared equally among the desired {circumflex over(r)} streams (transmitted along the columns of the determinedMU-precoder) and the remaining fraction 1−α of the transmit power willbe shared equally among the co-scheduled S-{circumflex over (r)}streams. The S-{circumflex over (r)} streams are transmitted alongmutually orthogonal vectors that are also orthogonal to the columns ofthe MU-precoder. The user 102 can report these additional CQI(s) alongwith the CQI(s) and PMI, RI determined using the SU-MIMO rules.

Here, it should be noted that, in another variant, the user 102 caninstead assume that the remaining fraction 1−α of the transmit powerwill be shared equally among S-r_(max) co-scheduled streams which aretransmitted along mutually orthogonal vectors that are also orthogonalto the columns of the MU-precoder. While the base station 104 need notbe aware of the exact rule used by the user 102, it should be aware ofthe fraction of the power the user 102 assumes for each of the streamsdirected to it while computing its SINRs.

6.2c

Any user that does not receive the semi-static signal from the basestation uses the SU-MIMO rules to determine its CQI(s) and PMI,RI. Sucha user only reports the set of CQI(s) and PMI,RI determined via theSU-MIMO rules. In this context, it is noted that low geometry users(i.e., users whose average received signal strength is below athreshold) are likely not suitable for MU-MIMO pairing and hence neednot be semi-statically signalled by the base station.

6.3

In aforementioned implementations, such as those described above insection 6.2, the parameter α can be a vector α of length r_(max) suchthat, while determining the SINRs under MU-rules for a precoder of ranks, 1≦s≦r_(max), the user 102 uses α(s) as the fraction. In addition, inboth the aforementioned cases in sections 6.1 and 6.2, the base station102 can signal another vector α^(SU) to the user 102 such that, indetermining the SINRs under SU-rules for a precoder of rank s, the user102 assumes that the total transmit power used to transmit its desiredsignals is α^(SU) (s)ρ and that no other stream intended for any otheruser is co-scheduled.

It should be noted that in the feed-forward signaling of S, r, α, (or S,r_(max), α) in order to reduce the signaling overhead, the system canuse different time-periods for signaling these three variables. In otherwords, the three variables need not always be jointly signaled and eachfeedforward signal can include a subset of the three variables. Theperiods and the choice of subset in each feedforward signal can beconfigured by the base station 104 and then informed to the user 102 viathe downlink 205. In such a case, while computing its feed back reportto the base station 104, the user 102 will use the most recentlyreceived value of each of the three variables. Also, in case any subsetof these variables are pre-determined and fixed and are known to/storedby all users and the base station 104 serving the users, that subsetneed not be signaled.

Similarly, the system can use steps to reduce the signaling overheadinvolved in the feed back reports, where, for example, each SU-reportconsists of SU-rank, SU-PMI and SU-CQIs, and each MU-report consists ofMU-rank, MU-PMI and MU-CQIs.

One such step includes feeding back the complete SU-report with areduced MU-feed back. This is made possible by forcing the MU-rank{circumflex over (r)} to be equal to min {r′,r} (or min {r′,r_(max)}),where r′ is the computed SU-rank. This is sensible, as r′ is the optimalrank that the user 102 deems it can support in the absence of intra-cellinterference from co-scheduled streams. Thus, the rank in the presenceof possible intra-cell interference should not exceed it.

To further reduce feed back overhead, as indicated above, theMU-precoder can be made to be a unique sub-matrix of the SU-precoder(i.e., the precoder determined under SU-MIMO rules) that is determinedvia pre-defined mapping rules. This will lead to a negligibleperformance degradation when r′≦r (or r′≦r_(max)), as the SU-precoderwill be a reasonably good choice because it approximates the first r′dominant right singular vectors of H^(†). Along similar lines, only oneset of complete MU feed back can be fed back accompanied by additionalCQI(s) computed under SU-MIMO rules for the MU-precoder.

Another approach that can be used for the MU and/or SU report is toemploy a longer feed back period for the rank compared to the feed backperiods of the respective PMI and CQI(s). Moreover, a feed back periodfor the PMI that is longer than the feed back period of the respectiveCQI(s) can be used. In such a case, while computing its schedulingdecisions, the base station 104 will use the most recently receivedrespective values of each variable in the report.

In addition, the system can restrict the user 102 to report one widebandPMI along with sub-band CQI(s). The sub-band PMI selection and sub-bandCQI computation rules can be modified in a straightforward manner toobtain the wide-band PMI selection and sub-band CQI computation rules.For example, with reference to FIG. 4, with continuing reference toFIGS. 2-3, an exemplary method 400 for determining a wideband precoderand corresponding channel quality indices is illustrated. The method 400can be performed at step 304 of the method 300 described above. Themethod 400 can begin at step 402, in which the processor 210 can usesub-band PMI selection and sub-band CQI computation rules to determine aPMI and CQI(s), as described above, for each sub-band. At step 404, theprocessor 210 can calculate a metric for each sub-band. For example, theprocessor 210 can calculate a sum rate for each sub-band. At step 406,the processor 210 can then select the PMI of the sub-band yielding ahighest metric for use as the wideband PMI. At step 408, using theprecoder identified by this PMI, the processor 210 can re-compute thesub-band CQI(s) using the sub-band CQI computation rules describedabove. The processor 210 may then proceed to step 306, where it candirect the transmitter 212 to transmit to the base station the wide-bandPMI and the recomputed CQIs.

7. Detailed Signaling Embodiment for DL Closed-Loop MU-MIMO

Turning now to a detailed signaling embodiment incorporating featuresdescribed above, it should be noted that, for downlink MU-MIMO, twotransmission modes, namely MIMO mode 3 (open loop MU-MIMO withnon-adaptive precoding) and MIMO mode 4 (closed loop MU-MIMO withadaptive precoding), have been defined in the 802.16m standard. Out ofthese two transmission modes, only MIMO mode 4 (CL MU-MIMO) permitstwo-stream simultaneous transmission to a scheduled advanced mobilestation (AMS) (a.k.a. UE or user-terminal or user). In particular, thereis one stream assignment with 3 total streams, there are three streamassignments with 4 total streams and eight stream assignments with 8total streams, that permit two-stream simultaneous transmission to oneor more co-scheduled AMS. The eight stream assignments with 8 totalstreams here is applicable to only an advanced base station (ABS)(a.k.a. eNodeB or eNB or base station) with eight transmit antennas.

For an ABS with polarized TX antennas, which has been identified as animportant configuration for practical deployment, the possibility ofscheduling an MU-MIMO AMS with 2 streams is particularly beneficial. Onthe other hand, there is no support for such two-stream (or two-layer)per-AMS transmission in the feed back obtained from each potentialMU-MIMO AMS. For supporting MU-MIMO, three MIMO feed back modes (MFM 5,6 and 7) have been defined in the 802.16m standard. Out of these, MFM 6targets CL (closed-loop) MU-MIMO with SLRU (sub-band logical resourceunit) or NLRU (mini-band logical resource unit) allocation. We note thatall of these three MFMs permit the feed back of (sub-band or wideband)PMI only from a rank-1 codebook. Moreover, the CQI is also computedassuming that the AMS will be served only one layer using therecommended PMI.

In accordance with exemplary aspects of the present principles describedabove, feed back support for CL MU-MIMO with two-layer transmission toone or more scheduled users can be enhanced. For example, for MU-MIMOfeed back modes with codebook-based feed back, a parameter α thatspecifies the power-split between the desired stream(s) and theinterfering streams that the AMS assumes can be defined. In particular,while computing its CQI, the AMS should assume that a fraction α of thetransmit power will be used by the ABS for transmitting its desiredstream(s), whereas the remaining fraction 1−α will be used to transmitthe interfering streams intended for the other co-scheduled users. Adefault value of a can denote an equal power split among all theco-scheduled streams. Examples of MFMs incorporating these aspects areprovided herein below.

The modified feed back allocation information element (IE) described inTable 1 below supports up-to rank-2 CL MU-MIMO PMI feed back bypermitting the ABS to suggest either rank-1 (space time coding rate-1(STC-rate 1)) or rank-2 (STC-rate 2) to a user using the MU-rank field.In addition, it includes a parameter α that specifies the power-splitbetween the desired stream(s) and the interfering streams. Inparticular, while computing its CQI, the AMS should assume that afraction α of the transmit power will be used by the ABS fortransmitting its (1 or 2) desired stream(s), whereas the remainingfraction 1−α will be used to transmit the (MaxMt-1 or MaxMt-2)interfering streams intended for the other co-scheduled users. IfMaxMt=MU-rank, the AMS feeds back MU-rank CL SU-MIMO CQI. In generalMaxMt>=MU-rank.

TABLE 1 Feed back Allocation A-MAP IE-v1 Syntax Size (Bit)Description/Notes if (MFM==6) or — — (MFM==7){ MaxMt 2 If Nt=4 (any MFM)0b00: 1 0b01: 2 0b10: 3 0b11: 4 If Nt=8 (MFM=6) 0b00: 1 0b01: 2 0b10: 40b11: 8 If Nt=8 (MFM=7) 0b00: 1 0b01: 2 0b10: 3 0b11: 4 } if (MFM==7){ α1 power split fraction 0b0: Equal split among MaxMt streams 0b1: ½ powerfor the desired stream and ½ power for the MaxMt-1 interfering streams }if (MFM==6){ — — MU-rank 1 Suggested rank 0b0: STC rate-1 0b1: STCrate-2 If (MU- rank<MaxMt){ A 1 power split fraction 0b01: Equal splitamong MaxMt streams 0b10: ½ power for the desired stream(s) and ½ powerfor the interfering streams  } }

In accordance another example, described below in Table 2, the modifiedfeed back allocation IE supports up-to rank-2 CL MU-MIMO PMI feed backby permitting the AMS to decide between rank-1 (STC-rate 1) or rank-2(STC-rate 2) precoding matrix feed back. In addition, it employs aparameter α that specifies the power-split between the desired stream(s)and the interfering streams. In particular, while computing its CQI, theAMS should assume that a fraction α of the transmit power will be usedby the ABS for transmitting its (1 or 2) desired stream(s), whereas theremaining fraction 1−α will be used to transmit the interfering streamsintended for the other co-scheduled users.

TABLE 2 Feed back Allocation A-MAP IE-v2 Syntax Size (bit)Description/Notes if (MFM==6) — — or (MFM==7){ MaxMt 2 If Nt=4 (any MFM)0b00: 1 0b01: 2 0b10: 3 0b11: 4 If Nt=8 (MFM=6) 0b00: 1 0b01: 2 0b10: 40b11: 8 If Nt=8 (MFM=7) 0b00: 1 0b01: 2 0b10: 3 0b11: 4 } if (MFM==7){ A1 power split fraction 0b00: Equal split among MaxMt streams 0b01: ½power for the desired stream and ½ power for the MaxMt-1 interferingstreams } if (MFM==6){ — — A 1 power split fraction with MU-rank (nogreater than the minimum of MaxMt and 2) being decided by the AMS 0b01:Equal split among MU-rank streams 0b01 : If MaxMt=MU-rank then  Equalsplit among MU-rank streams Else (MaxMt>MU-rank) ½ power for the desiredMU-rank stream(s) and ½ power for the interfering (MaxMt-MU-rank)streams }

In accordance with another example, described below in Table 3, themodified feed back formats for MFM 6 support up-to rank-2 CL MU-MIMO PMIfeed back by permitting the AMS to decide between rank-1 (STC-rate 1) orrank-2 (STC-rate 2) precoding matrix feed back. In particular, the AMSreports a preferred MU-rank in a long-term report (with a configurablelong term period). In addition, the subsequent sub-band PMIs in theshort term reports from the AMS correspond to the codebook of thereported MU-rank.

TABLE 3 Feed back formats for MFM 6-v2a Feed Number back of Report Feedback Format FBCH reports period fields Notes 0(M=1) PFBCH 3 ShortSubband CQI or Encoding type 0 any type of EDI No short term report whenq=0 Short Subband PMI Encoding type 0 No short term report when q=0 LongBest subbands Encoding type 1 index MU-rank 1(M=2) SFBCH 2 Short For(m=1:M){ No Short term Subband report differential CQI, when q=0 subbandPMI} Long Best subbands index, subband avg CQI, PFBCH indicator MU-rank2(M=3) SFBCH 2 Short For (m=1:M){ No Short term Subband report when q=0differential CQI, subband PMI} Long Best subbands index, subband avgCQI, PFBCH indicator MU-rank 3(M=4) SFBCH 2 Short For (m=1:M){ No Shortterm Subband report when q=0 differential CQI, subband PMI} Long Bestsubbands index, subband avg CQI, PFBCH indicator MU-rank

In accordance with another example, described below in Table 4, themodified feed back formats for MFM 6 support up-to rank-2 CL MU-MIMO PMIfeed back by permitting the AMS to decide between rank-1 (STC-rate 1) orrank-2 (STC-rate 2) precoding matrix feed back. In particular, the AMSreports a preferred MU-rank in each short-term report (with aconfigurable short-term period). In addition, the subband PMI includedin that short term report corresponds to the codebook of the reportedMU-rank.

TABLE 4 Feed back formats for MFM 6-v2b Feed Number back of Report Feedback Format FBCH reports period fields Notes 0(M=1) PFBCH 3 ShortSubband CQI or Encoding type 0 any type of EDI No short term report whenq=0 Short Subband PMI Encoding type 0 MU-rank No short term report whenq=0 Long Best subbands Encoding type 1 index l(M=2) SFBCH 2 Short For(m=1:M){ No Short term Subband report when q=0 differential CQI, subbandPMI, MU rank} Long Best subbands index, subband avg CQI, PFBCH indicator2(M=3) SFBCH 2 Short For (m=1:M){ No Short term Subband report when q=0differential CQI, subband PMI, MU-rank} Long Best subbands index,subband avg CQI, PFBCH indicator 3(M=4) SFBCH 2 Short For (m=1:M){ NoShort term Subband report when q=0 differential CQI, subband PMI,MU-rank} Long Best subbands index, subband avg CQI, PFBCH indicator

8. Scheduling at the Base Station

Referring now to FIG. 5 with continuing reference to FIGS. 1-3, a method500 for scheduling MU-MIMO users in an OFDMA system is illustrated. Inparticular, the base station 104 can be configured to implement themethod 500, which can complement the method 300 described above. Themethod 500 can begin at step 502 in which the controller 206 can directthe transmitter 208 to transmit scheduling parameters for one or moresub-bands to each prospective user. For example, as described above,such parameters for any particular user 102 can include an indication ofany one or more of an estimate of (or an upper bound on) the totalnumber of streams (s) that the base station will schedule on a sub-band,a suggested precoding matrix rank (r) for a particular user 102, amaximum rank (r_(max)) for the particular user 102, an estimate of theper-RB total power (ρ) of signals transmitted to all users co-scheduledwith the particular user 102 and the fraction (α) of the total powerthat will be employed for the data signals directed to the particularuser 102. Here, the controller 206 can employ the scheduler 204 todetermine the scheduling parameters using, for example, methodsdescribed in the above-referenced co-pending utility applications.

At step 504, the receiver 208 of the base station 104 can receive, fromeach prospective user 102, indications of a preferred PMI and/orSINR/CQI based on any one or more of the parameters transmitted at step502. For example, the indications can be the same indications that canbe transmitted by the user 102 at step 306, as described above.

At step 506, the scheduler 204 can select an appropriate set of theprospective users to schedule and can determine scheduling informationfor the selected users. Such scheduling information can include atransmit precoder and an assigned rate for each user and/or each stream.

In order to compute the scheduling information, the base station shouldbe able to compute an estimate of the SINR for each co-scheduled streamin each choice of user set and associated transmit precoders. A methodfor computing such an estimate is described herein below. It should benoted that the method described below can be performed by the scheduler204. The method permits the scheduler 204 of the base station 104 toco-schedule an arbitrary number of streams (not necessarily equal to thevalue S that was conveyed to the users) along arbitrary transmitprecoders. In particular, suppose that the base station 104 considersco-scheduling Q users, for example user-1 to user-Q, who have reportedprecoders {Ĝ_(j)}_(j=1) ^(Q), respectively. Also assume all users employlinear MMSE receivers and let H₁ ^(†) to H_(Q) ^(†) represent thechannels seen by users 1 to Q, respectively. Let V_(j)=[v_(j) ¹, . . . ,v_(j) ^(r) ^(j) ] denote the M×r_(j) transmit precoder (of rank r_(j)and with unit-norm columns) that the base station 104 intends to employfor user j, 1≦j≦Q such that R′=Σ_(j=1) ^(Q)r_(j)≦M. Define A=└V₁, V₂, .. . , V_(Q)┘. It can be shown that the true SINR seen by user-j for itsi^(th) stream that is transmitted along v^(i) _(j) is given by

sin=^(i) _(j)={circumflex over (ρ)}v^(i†) _(j) H _(j)(I+{circumflex over(ρ)}H _(j) ^(†)(AA ^(†) −v ^(i) _(j) v ^(i†) _(j))H _(j))⁻¹ H _(j) ^(†)v ^(i) _(j)  (24)

where {circumflex over (ρ)}=ρ/R′ is the power per stream. Then, thefollowing simple but useful lemma provides an alternate expression forthe SINR given in (24).

Lemma 2 The true SINR seen by user-j for its i^(th) stream is equal to

$\begin{matrix}{{{\sin \; r_{j}^{i}} = \frac{\alpha_{j}^{i}}{1 - \alpha_{j}^{i}}}{\alpha_{j}^{i} = \left\lbrack {\left( {I + {A^{\dagger}R_{j}A}} \right)^{- 1}A^{\dagger}R_{j}A} \right\rbrack_{{{\sum\limits_{m = 1}^{j - 1}r_{m}} + i},{{\sum\limits_{m = 1}^{j - 1}r_{m}} + i}}}{{for}\mspace{14mu} {all}\mspace{14mu} i} = {{\left\{ {1,\ldots \mspace{14mu},r_{j}} \right\} \mspace{14mu} {and}\mspace{14mu} {where}\mspace{14mu} R_{j}} = {\hat{\rho}\; H_{j}{H_{j}^{\dagger}.}}}} & (25)\end{matrix}$

An important consequence of (25) is that the BS 104 can approximate thematrix R_(j) by {circumflex over (R)}_(j) and then determine approximateSINRs as

$\begin{matrix}{{{\hat{\sin}\; r_{j}^{i}} = \frac{{\hat{\alpha}}_{j}^{i}}{1 - {\hat{\alpha}}_{j}^{i}}}{{\hat{\alpha}}_{j}^{i} = \left\lbrack {\left( {I + {A^{\dagger}{\hat{R}}_{j}A}} \right)^{- 1}A^{\dagger}{\hat{R}}_{j}A} \right\rbrack_{{{\sum\limits_{m = 1}^{j - 1}r_{m}} + i},{{\sum\limits_{m = 1}^{j - 1}r_{m}} + i}}}} & (26)\end{matrix}$

Here we employ the following approximation

$\begin{matrix}{{{R_{j} \approx {\hat{R}}_{j}}\overset{\Delta}{=}{{\hat{G}}_{j}{\hat{D}}_{j}{\hat{G}}_{j}^{\dagger}}},{\forall j},{{{where}\mspace{14mu} {\hat{D}}_{j}} = {{diag}\left\{ {{\gamma_{j}{\hat{SINR}}_{j}^{1}},\ldots \mspace{14mu},{\hat{SINR}}_{j}^{r_{j}^{\prime}}} \right\}}}} & (27)\end{matrix}$

and r′_(j)≧1 is the rank of Ĝ_(j). {SI{circumflex over (N)}R^(i) _(j)}are the SINRs reported by user i after quantizing SINRs determined using(5) or (13). γ_(j) is a scaling factor such that γ_(j)=S/R′ if user jemploys (5) and γ_(j)=r′_(j)/R′ when the user employs (13) instead.

Remark 1 Note that the approximation in (27) attempts to obtain the bestrank r′_(j) approximation of R_(j) based one the feed back of user-j.Clearly the best rank r′_(j) approximation of R_(j) is the matrix formedwhen Ĝ_(f) contains the r′_(j) dominant eigenvectors of R_(j) and{circumflex over (D)}_(j) contains the r′_(j) dominant eigenvalues. Itcan be verified that {circumflex over (R)}_(j) approaches R_(j) as thecodebook and quantization resolution improve. Note however, that evenunder the best rank r′_(j) approximation of R_(j), si{circumflex over(n)} r^(i) _(j) can be different from sin r^(i) _(j) ifr′_(j)<Rank(R_(j)).

Remark 2 Under the approximation in (27) and (25), user-j sees nointerference from co-scheduled user-q if V_(j) ^(†)V_(q)=0.

After the base station 104 computes the scheduling information at step506, the controller 206 of the base station 104 can direct thetransmitter 208 to transmit the respective scheduling information to theselected users.

Having described preferred embodiments of MU-MIMO-OFDMA methods andsystems for signaling multi-rank CQIs and precoders (which are intendedto be illustrative and not limiting), it is noted that modifications andvariations can be made by persons skilled in the art in light of theabove teachings. It is therefore to be understood that changes may bemade in the particular embodiments disclosed which are within the scopeof the invention as outlined by the appended claims. Having thusdescribed aspects of the invention, with the details and particularityrequired by the patent laws, what is claimed and desired protected byLetters Patent is set forth in the appended claims.

What is claimed is:
 1. A method for determining attributes ofcommunication channels of multi-user (MU)-multiple input multiple output(MIMO) users in an orthogonal frequency division multiplexing basedmultiple access (OFDMA) system, the method comprising: receiving from abase station, for at least one sub-band of contiguous sub-carriers, anindication of an estimate of or an upper-bound on a total number ofstreams that are co-scheduled by the base station on the at least onesub-band or an indication of a fraction (α) of a transmit power at thebase station that is applied to streams that are scheduled fortransmission to a particular user; determining one or more signalquality measures for the at least one sub-band based on at least one ofthe fraction or the estimate of or the upper-bound on the total numberof streams that are scheduled by the base station on the at least onesub-band; and transmitting to the base station an indication of the oneor more signal quality measures.
 2. The method of claim 1, wherein thesignal quality measures are signal-to-interference-plus-noise ratios(SINRs), the indication of the one or more signal quality measures is anindication of one or more channel quality indices (CQIs) that are basedon the SINRs, and wherein the method further comprises: determining aprecoder matrix for the at least one sub-band based on at least one ofthe fraction or the estimate of or the upper-bound on the total numberof streams that are scheduled by the base station on the at least onesub-band, wherein the transmitting further comprises transmitting to thebase station an indication of the precoder matrix.
 3. The method ofclaim 2, wherein the receiving further comprises receiving an indicationof a suggested or an upper-bound precoder rank and wherein thedetermining one or more signal quality measures and the determining theprecoder matrix is further based upon at least one of the fraction, thesuggested or upper-bound precoder rank, or the estimate of or theupper-bound on the total number of streams that are scheduled by thebase station on the at least one sub-band.
 4. The method of claim 3,wherein at least one of the precoder matrix or the one or more SINRs aredetermined under the assumption that a remaining fraction of thetransmit power is 1−α and is assigned to streams that are scheduled fortransmission to users co-scheduled with the particular user.
 5. Themethod of claim 4, wherein at least one of the precoder matrix or theone or more SINRs are determined under the assumption that the streamsthat are scheduled for transmission to the particular user are allocatedequal power and that the streams that are scheduled for transmission tothe users co-scheduled with the particular user are allocated equalpower.
 6. The method of claim 3, wherein the precoder matrix isdetermined in accordance with at least one of single-user schedulingrules or multi-user scheduling rules, wherein the one or more signalquality measures are determined in accordance with at least one of thesingle-user scheduling rules or the multi-user scheduling rules andwherein the transmitting further comprises transmitting at least one tagidentifying each signal quality measure as being determined inaccordance with the single-user scheduling rules or the multi-userscheduling rules and at least one other tag identifying the precodermatrix as being determined in accordance with the single-user schedulingrules or the multi-user scheduling rules.
 7. The method of claim 6,wherein the precoder matrix and the one or more SINRs are determinedunder the multi-user scheduling rules.
 8. The method of claim 7, whereinthe determining one or more signal quality measures further comprisesdetermining one or more other signal quality measures in accordance withthe single-user scheduling rules based on the precoder matrix andwherein the transmitting further comprises transmitting an indication ofthe one or more other signal quality measures.
 9. The method of claim 6,wherein the precoder matrix and the one or more SINRs are determinedunder the single-user scheduling rules, wherein the method furthercomprises determining one or more other signal quality measures inaccordance with the multi-user scheduling rules based on the precodermatrix and wherein the transmitting further comprises transmitting anindication of the one or more other signal quality measures.
 10. Themethod of claim 9, wherein the precoder matrix is a first precodermatrix, wherein the method further comprises determining a secondprecoder matrix based on the first precoder matrix in accordance withthe multi-user scheduling rules and wherein the transmitting furthercomprises transmitting an indication of the second precoder matrix tothe base station.
 11. The method of claim 9, wherein the determining thefirst precoder matrix comprises determining an other rank as the rankfor the first precoder matrix, wherein the determining the secondprecoder matrix comprises selecting the minimum rank between thereceived rank and the other rank as the rank for the second precodermatrix and wherein the transmitting further comprises transmitting anindication of the other rank to the base station.
 12. The method ofclaim 11, wherein the determining the second precoder matrix comprisesdetermining a sub-matrix of the first precoder matrix as the secondprecoder matrix.
 13. A method for determining precoders forcommunication channels of multi-user (MU)-multiple input multiple output(MIMO) users in an orthogonal frequency division multiplexing basedmultiple access (OFDMA) system, the method comprising: receiving from abase station, for at least one sub-band of contiguous sub-carriers, anindication of an estimate of or an upper-bound on a total number ofstreams that are co-scheduled by the base station on the at least onesub-band and an indication of a fraction (α) of a transmit power at thebase station that is applied to streams that are scheduled fortransmission to a particular user; determining a precoder matrix for theat least one sub-band based on at least one of the fraction or theestimate of or the upper-bound on the total number of streams that arescheduled by the base station on the at least one sub-band; andtransmitting to the base station an indication of the precoder matrix.14. The method of claim 13, wherein the method further comprisesdetermining one or more signal quality measures for the at-least onesub-band based on at least one of the fraction or the estimate of or theupper-bound on the total number of streams that are scheduled by thebase station on the at least one sub-band, wherein the transmittingfurther comprises transmitting to the base station an indication of theone or more signal quality measures.
 15. The method of claim 14, whereinthe signal quality measures are signal-to-interference-plus-noise ratios(SINRs), the indication of the one or more signal quality measures is anindication of one or more channel quality indices (CQIs) that are basedon the SINRs.
 16. The method of claim 14, wherein the receiving furthercomprises receiving an indication of a suggested or an upper-boundprecoder rank and wherein the determining one or more signal qualitymeasures and the determining the precoder matrix is further based uponat least one of the fraction, the suggested or upper-bound precoderrank, or the estimate of or the upper-bound on the total number ofstreams that are scheduled by the base station on the at least onesub-band.
 17. The method of claim 16, wherein at least one of theprecoder matrix or the one or more signal quality measures aredetermined under the assumption that a remaining fraction of thetransmit power is 1−α and is assigned to streams that are scheduled fortransmission to users co-scheduled with the particular user.
 18. Themethod of claim 17, wherein at least one of the precoder matrix or theone or more SINRs are determined under the assumption that the streamsthat are scheduled for transmission to the particular user are allocatedequal power and that the streams that are scheduled for transmission tothe users co-scheduled with the particular user are allocated equalpower.
 19. The method of claim 18, wherein the precoder matrix isdetermined in accordance with at least one of single-user schedulingrules or multi-user scheduling rules, wherein the one or more signalquality measures are determined in accordance with at least one of thesingle-user scheduling rules or the multi-user scheduling rules andwherein the transmitting further comprises transmitting at least one tagidentifying each signal quality measure as being determined inaccordance with the single-user scheduling rules or the multi-userscheduling rules and at least other one tag identifying the precodermatrix as being determined in accordance with the single-user schedulingrules or the multi-user scheduling rules.
 20. A receiver system fordetermining attributes of communication channels of multi-user(MU)-multiple input multiple output (MIMO) users in an orthogonalfrequency division multiplexing based multiple access (OFDMA) systemcomprising: a receiver configured to receive from a base station, for atleast one sub-band of contiguous sub-carriers, an indication of anestimate of or an upper-bound on a total number of streams that areco-scheduled by the base station on the at least one sub-band or anindication of a fraction of a transmit power at the base station that isapplied to streams that are scheduled for transmission to a particularuser; a processor configured to determine one or more signal qualitymeasures for the at least one sub-band based on at least one of thefraction or the estimate of or the upper-bound on the total number ofstreams that are scheduled by the base station on the at least onesub-band; and a transmitter configured to transmit to the base stationan indication of the one or more signal quality measures.